Supply-chain management system

ABSTRACT

An Internet-based computer-assisted supply-chain management system (SCMS) replaces the archaic commerce systems presently in use. It coordinates just-in-time distribution of items purchased by consumers from a plurality of merchants whereby the inventory in the distribution pipeline is reduced to inventory in transport. It uses regional distributions centers and neighborhood order aggregation facilities for an efficient transfer of items to consumers. Consumers can pick up aggregated orders at an order aggregation facility or have them delivered at a residence. The SCMS phases out conventional checkout registers in favor of web browsers with automatic transaction execution. Retailers can operate with little or no inventory. Window shops facilitate promotion of items and help consumers make selections and decisions with respect to purchases they may be contemplating. The SCMS provides real-time consumption monitoring and forecasts, significantly reduces supply-chain costs and retail prices, promotes economic growth, and minimizes undesirable cyclic economic fluctuations.

RELATED APPLICATIONS

This application is related to but does NOT claim priority to U.S.application Ser. No. 11/799,436 filed on May 1, 2007, which bears thesame title, specification, and drawings as the present application.

FIELD OF THE INVENTION

This invention relates generally to a new age Internet-basedsupply-chain management system configured to support just-in-timedistribution of items to consumers, reduce inventory levels, reducetransportation costs, collect consumption data in real-time, predictfuture consumption, distribute consumption forecasts to merchants,facilitate promotion and advertising, facilitate the transfer of itemsto consumers, reduce overall supply-chain costs, and save consumers timeand money.

BACKGROUND OF THE INVENTION

The conventional distribution of items to consumers is, and always hasbeen, a most inefficient process that results in retail prices one orderof magnitude higher than the manufacturing costs, wastes a considerableportion of available energy resources, wastes a significant amount ofconsumers' time, and limits the conveniences that can be offered toconsumers.

SUMMARY OF THE INVENTION

The present invention addresses the problems previously outlined byintegrating in a new age Internet-based supply-chain management systemconcepts that support an efficient system for distributing items toconsumers.

One aspect of the invention relates to an order aggregation facilitywhich is a commercial establishment configured to receive, temporarilystore, physically aggregate, and transfer to a consumer batches of itemspurchased by the consumer from different merchants.

One aspect of the invention relates to an order aggregation managementsub-system that manages activities associated with transfers of itemsfrom a plurality of manufacturers and producers to a network of orderaggregation facilities around the country.

One aspect of the invention relates to computer programs for managingand coordinating transportation operations for a plurality of carriersthat support just-in-time distribution of items to consumers.

One aspect of the invention relates to an integrated inventory sharingsub-system configured to help merchants reduce required operatinginventories, balance inventories, reduce inventory costs, and fulfillconsumer orders in the case of inventory shortages.

One aspect of the invention relates to a predictive ordering consumptionforecasting sub-system, also referred to herein as “predictive orderingsub-system” whereby consumers are given a predictive price discount inexchange for ordering items at an order date and accepting delivery at alater delivery date.

One aspect of the invention relates to the generation of accurateconsumption forecasts derived from the predictive ordering sub-system.

One aspect of the invention relates to a consumption cruise controlsub-system that reduces undesirable fluctuations in item consumption.

One aspect of the invention relates to a consumer preference codesub-system that facilitates online shopping of non-uniform generic itemsand ensures that consumers get the items that match their preferences.

One aspect of the invention relates to a window shop managementsub-system which coordinates the operation of a plurality of windowshops configured to provide merchants with promotional and displayfacilities and services that help consumers make selections anddecisions with respect to items they may be interested in acquiring.

One aspect of the invention relates to a decentralized exhibition systemthat offers merchants a network of collaborating window shops wheremerchants can promote and display their items to consumers, make newitem introductions, and market test new items.

One aspect of the invention relates to a supply-chain managementsub-system that manages and coordinates the operations of thesupply-chain management system.

Deployment of business models based on the above concepts can encourageconsumers to shop online and can produce numerous benefits. Among thesebenefits, the most important are significant reductions in itemdistribution costs as well as the time, effort, and energy consumersspend shopping.

All participants in the supply-chain management system, such asmanufacturers, producers, wholesalers, distributors, retailers, onlineretailers, storefronts, service providers, and consumers can derivelarge benefits from this invention. Manufacturers and producers canobtain accurate real-time data upon which to base manufacturing andproduction plans. Using a just-in-time business model, wholesalers,distributors, and retailers can operate efficiently, with minimalinventories, item costs, shipping costs, and shipping times. Retailerscan ensure that no sales are lost due to lack of inventory and canbetter serve their customers with broader item selections. At the end ofthe distribution chain, consumers can shop comfortably from home, buyitems at more competitive prices, and receive their purchases morequickly with little or no need to drive for shopping.

The present invention takes advantage of recent advances in computer andInternet technology to provide the foundation necessary for electroniccommerce to become one of the most significant factors in improvingproductivity an enhancing economic prosperity during this century.Further aspects of this invention will become apparent in the DetailedDescription and by reference to the attached drawings. The DetailedDescription contains the following Sections:

I. Overview

A. Shopping models

B. Inventory models

C. Transfer models

D. Promotional models

E. Retail models

F. Consumption monitoring and forecasting models

II. Major components of the supply-chain management system

A. The Order Aggregation Management Sub-system

B. The Integrated Inventory Sharing Sub-System

C. The Predictive Ordering Consumption Forecasting Sub-System

D. The Consumer Preference Code Sub-System

E. The Window Shop Management Sub-System

F. The Supply-Chain Management Sub-System

III. Operation of the supply-chain management system

A. Operation of the order aggregation management sub-system

B. Operation of the integrated inventory sharing sub-system

C. Operation of the predictive ordering consumption forecastingsub-system

D. Operation of the consumer preference code sub-system

E. Operation of the window shop management sub-system

F. Operation of the supply-chain management sub-system

IV. Conclusion

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram of a preferred embodiment of thesupply-chain management system.

FIG. 2 illustrates a block diagram of a preferred embodiment of theorder aggregation management sub-system.

FIG. 3 illustrates a block diagram of a preferred embodiment of theintegrated inventory sharing sub-system.

FIG. 4 illustrates a block diagram of a preferred embodiment of thepredictive ordering consumption forecasting sub-system.

FIG. 5 illustrates a block diagram of a preferred embodiment of theconsumer preference code sub-system.

FIG. 6 illustrates a block diagram of a preferred embodiment of thewindow shop management sub-system.

FIG. 7 illustrates a block diagram of a preferred embodiment of thesupply-chain management sub-system.

FIG. 8 illustrates a block diagram depicting the six basic sub-systemcomponents and seven physical elements that are an integral part of theoperation of the supply-chain management system.

FIG. 9 provides a diagrammatical representation of the operation of thecarrier services.

FIGS. 10A-C illustrate an order aggregation method preferably performedby the order aggregation management sub-system.

FIG. 11 illustrates an integrated inventory sharing method preferablyperformed by the integrated inventory sharing sub-system.

FIG. 12 illustrates a preferred predictive ordering method for using thepredictive ordering sub-system.

FIG. 13 illustrates a hypothetical three dimensional plot of % costsavings versus predictive order delay and predictive order volume.

FIG. 14 illustrates a hypothetical three dimensional correlation ofpredictive order volume versus predictive order delay and predictiveprice discount.

FIG. 15 illustrates a predictive price discount optimization methodpreferably performed by the predictive ordering sub-system.

FIG. 16 illustrates a block diagram of a preferred embodiment of analgorithmic closed loop control system for consumption cruise control.

FIGS. 17A-B illustrate a preferred consumption cruise control processperformed by the algorithmic closed loop control system.

FIG. 18 depicts an exemplary illustration of a web page that can be usedby a consumer to set up preference codes for a non-uniform generic item.

FIG. 19 illustrates a preferred method for registering consumerpreference codes.

FIG. 20 illustrates a preferred method for using consumer preferencescodes.

FIGS. 21A-21C illustrate a preferred method for the operation of thewindow shop management sub-system and the window shops.

FIGS. 22A-B illustrate a preferred method for the operation of thesupply-chain management sub-system.

DETAILED DESCRIPTION OF THE INVENTION

In the following description, reference is made to the accompanyingdrawings, which form a part hereof, and which show, by way ofillustration, specific embodiments or processes in which the inventionmay be practiced. Where possible, the same reference numbers are usedthroughout the drawings to refer to the same or like components. In someinstances, numerous specific details are set forth in order to provide athorough understanding of the present invention. The present invention,however, may be practiced without the specific details or with certainalternative equivalent devices and methods to those described herein. Inother instances, well-known methods and devices have not been describedin detail so as not to unnecessarily obscure aspects of the presentinvention.

DEFINITIONS

For the purposes of the invention, the following stated definitionsshall be construed as applying to the specification and to the Claims:

Definition: an item is a product or a service a consumer can purchase.

Definition: a merchant is any business entity that sells items orservices. A merchant can be, for example, a manufacturer, a producer, awholesaler, a distributor, a retailer, an online retailer, a storefront,and a service provider.

Definition: a purchase order is a documented transaction between aconsumer and a merchant, whereby the consumer agrees to purchase fromthe merchant one or more items or services and the merchant agrees toprovide to the consumer each of the one or more items purchased by theconsumer at an identified place and time.

I. OVERVIEW

The invention describes a new age Internet-based supply-chain managementsystem to replace the archaic commerce systems that have been in use inuse for many years. The operation of the supply-chain management systeminvolves new operating models that affect all the participants in thesupply-chain from the manufacturers and producers that provide thesupply to the consumers that create the demand for the supply. Theinvention provides flexibility for a transition phase during which theparticipants in the supply-chain management system adjust to the newoperating models. During the transition phase, the supply-chainmanagement system can still provide significant benefits to earlyparticipants even before full deployment of the supply-chain managementsystem is completed. Considering that the younger generation is rapidlyembracing the benefits of a computer-based way of life, the transitionphase is not expected to encounter major difficulties. The new operatingmodels are classified in categories and each category is describedseparately to provide a clear overview of the substance of theinvention.

A. Shopping Models

In a preferred embodiment of the invention, consumer shopping isperformed online via web browsers that access shopping platformsconfigured to support online transactions between consumers andmerchants participating in the supply-chain management system. Aconsumer can use a home computer to shop online, can use computerterminals made available to consumers in retail establishments to shoponline, and can use the services of a sales person in a retailestablishment to book, via a web browser, purchase orders for the itemsthe consumer whishes to purchase. The important issue is to make thetransition out of the conventional checkout registers and progress tothe online systems proposed in the invention. The transition involvesextending online shopping to include local retailers where consumers domost of their shopping, whereby retailers replace their conventionalcheckout registers by shopping browsers.

Predictive ordering is another shopping model provided by thesupply-chain management system that will have a significant impact onproductivity and on stable economic growth. Manufacturers and producersof items could achieve large productivity gains if they could haveaccurate forecasts of consumption. Information on future consumptionexists today buried in the minds of consumers. However, this preciousinformation is wasted every day because it is not collected. Predictiveordering replaces the conventional discount coupons and promotionaldiscounts by a system whereby consumers are given significant pricediscounts for ordering items in advance of delivery. Preferably, theprice discounts vary with the time span between the order date and thedelivery date and are based upon a cost savings realized primarily bymanufacturers and producers and secondarily by other participants of thesupply-chain as a result of the advanced knowledge of the purchases.Since consumers in the US are very sensitive to price discounts, it isexpected that an increasing fraction of the consumers will takeadvantage of predictive ordering. The resulting predictive ordering datawill provide a very large sample of the expected consumption which canbe combined with historical data from non-predictive purchases to deriveaccurate projections of future consumption. To help the consumer, apredictive ordering sub-system can provide a shopping list generationprogram that automatically generates a suggested shopping list for theconsumer based upon the consumer's shopping history. The list can beautomatically restarted after each online shopping session and presentedto the consumer for review and edit. After the consumer edits andapproves the shopping list, another program can automatically do theshopping with no further action required by the consumer.

Consumer preference codes provide another shopping model that allowsconsumers to shop online for non-uniform items such as fresh produce,halibut, and New York steak with confidence that the items they receivewill meet their expectations. In a preferred embodiment of a consumerpreference code sub-system, each class of such non-uniform items,represented by a generic name that is insufficient to characterize thespecific consumer preferences, is divided in sub-classes. Each sub-classis representative of a different consumer preference and ischaracterized by a set of quantifiable characteristics, whereby eachcharacteristic is given a range of discrete values. Thissub-classification results in a table that provides for each particularsub-class the value of each characteristic for the particular sub-class.Once the table is established, each sub-class can be designated by thegeneric name followed by the value of each of the quantifiablecharacteristics used to define the sub-class. For convenience, thesystem can be configured for the consumer to provide an optionalpersonalized name the consumer can use as shorthand to order anon-uniform generic item of the sub-class the consumer prefers.

B. Inventory Models

Inventory is a counter productive and costly legacy inherited from thedays when society did not benefit from mechanized transportation,computer systems, and telecommunications. The daily costs of holding anitem in inventory in a warehouse or on a shelf in a retail storerepresent an important part of the retail price of the item, which ispassed on to consumers. Except for items that may require aging such aswines and spirits, most items don't get better while in inventory andsome like perishables actually get much worse. For example, in asupermarket the spoilage of produce is typically 30%.

In a preferred embodiment of the invention, inventory is significantlyreduced if not eliminated at every link of the supply-chain. Thesupply-chain management system relies upon a just-in-time distributionsystem whereby the inventory in the supply-chain is practically reducedto the items that are physically being transported from a point oforigin to the consumer.

Integrated inventory sharing is an inventory model that helps merchantsreduce required operating inventories, balance inventories, reduceinventory costs, and fulfill consumer orders in the case of an inventoryshortage. According to this model, a plurality of merchantsparticipating in the integrated inventory sharing sub-system shareinventories to create a virtual inventory that is available to eachmerchant. Preferably a database is used to maintain in real-timeinventory sharing data and a server is used to support the operation ofan integrated inventory sharing sub-system. On a regional basis, aregional virtual inventory pool can be maintained, whereby aparticipating merchant in the region will be able to fulfill ordersrequiring immediate delivery irrespective of the inventory status heldby the merchant.

In addition to reducing inventory costs, the integrated inventorysharing sub-system gives each merchant the opportunity to sell to itsclientele a broad selection of items available in the virtual inventorythat no merchant would have sufficient shelf space to inventory. Toillustrate, consider the following example of men's slacks:

Number of possible waist sizes=23

Number of possible inseam sizes=5

Number of color selections=4

Number of possible styles=20

Number of possible brands=100

The product of these values equates to 920,000 possible variations ofmen's slacks a consumer could purchase. Assuming that a retailer wouldinventory 5 items for each variation to satisfy random demand, the totalaverage inventory for the retailer would equate to 4,600,000 pairs ofslacks. This number emphasizes two fundamental absurdities in connectionwith the value of inventory and the space occupied by inventory. At anaverage of $30 per pair, the value of inventory would represent$138,000,000 or several orders of magnitude the potential annual salesof slacks realizable by the retailer. To store the 4,600,000 pairs ofslacks it would require 1,500,000 cubic feet or a cube with an edge ofapproximately 114 feet.

These numbers clearly show why retailers can only afford to inventory avery limited selection of each type of item they sell. Over the yearsretailers have learned which items experience the largest volume ofsales in their location and they limit their retail to those items.Because of fluctuations in consumption, items a consumer purchasesregularly may suddenly disappear from the shelves and be replaced byanother item that has recently increased in sales volume. This effect,which could be called the shelf space syndrome, is very frustrating forconsumers and costs the industry a significant loss of revenue due tomissed opportunities. By contrast, with the deployment of thesupply-chain management system any consumer will be able to obtain anyitem at any time from any location in the country with a few simpleclicks.

C. Transfer Models

Transfer models relate to the transfer of items from manufacturers andproducers to the consumers who purchase the items. The most crucialtransfer model of this invention is order aggregation. In a preferredembodiment of this model, each consumer purchases items from differentlocal and out of town merchants using the online shopping modelsdescribed above. All these items originally come from shippingfacilities of manufacturers and producers that provide the items. Theitems originating from a given shipping facility can be combined in oneor more shipments that are destined to consumers in a given regionalarea. In the regional area, a regional distribution center that servicesthe regional area can receive the shipments. From the regionaldistribution center the items are then transferred to various orderaggregation facilities that service neighborhoods within the regionalarea. These transfers can be executed in accordance with just-in-timeschedules managed by an order aggregation management sub-systemresponsible for coordinating the operation of carrier servicesparticipating in the supply-chain management system.

In a preferred embodiment of this model, the order aggregation facilityis a commercial establishment equipped with facilities, which includethe following:

-   -   (a) Temporary storage environments at room, cold, and frozen        temperature for items purchased by consumers from any number of        merchants.    -   (b) A control center housing computer systems configured to        communicate with a supply-chain management sub-system to        coordinate the operations of the order aggregation facility.    -   (c) An order aggregation area configured to perform the physical        aggregation of items purchased by consumers from different        merchants.    -   (d) Truck loading and unloading docks.    -   (e) Consumer vehicle stations for consumers to pick up        physically aggregated items, deliver returns, and send parcels.    -   (f) A consumer service area configured to facilitate interaction        between consumers and order aggregation facility personnel.

From a functional perspective, the order aggregation facility ispreferably configured to perform functions, which include the following:

-   -   (a) Communicate with the supply-chain management sub-system to        receive data and instructions, coordinate activities, and        provide reports.    -   (b) Receive shipments of items delivered by carriers.    -   (c) Temporarily store each of the items delivered by carriers in        a proper environment.    -   (d) Physically execute aggregation of the items delivered by        carriers in accordance with aggregation instructions.    -   (e) Transfer to a consumer a batch of physically aggregated        items when the consumer elects to pick up the batch of        physically aggregated items at the order aggregation facility.    -   (f) Send via a carrier service a batch of physically aggregated        items to an address designated by the consumer when the consumer        elects to have the batch of physically aggregated items        delivered.

To save the consumer time and driving expense, the consumer can provideaggregation instructions whereby the items purchased by the consumerfrom various merchants are transferred just-in-time to an orderaggregation facility to be physically aggregated in one or more batchesbefore being transferred to the consumer. After aggregation, each batchof physically aggregated items can be transferred from the orderaggregation facility to the consumer, preferably at a date and timeselected by the consumer.

The consumer has two options to receive each batch of physicallyaggregated items at the selected date and time. One is to pick up thebatch of physically aggregated items at the order aggregation facility.Another is to have the batch of physically aggregated items delivered toan address designated by the consumer. Preferably, if the consumerelects to pick up the batch of physically aggregated items, the consumerselects the order aggregation facility else the order aggregationmanagement sub-system makes the selection.

For example, a consumer purchases online a large TV, a large microwaveoven, various food items, a shirt, and two books from different stores.The consumer may elect to pick up the small items on a Wednesday at 5:40PM at an order aggregation facility that is on the way home from work,and have the large items delivered at 6:15 PM when the consumer is sureto be home. To comply with the consumer's instructions, all the itemspurchased by the consumer would be scheduled to arrive at the selectedorder aggregation facility around 5:00 PM. Alternatively, the consumercould decide to have the large items delivered at a residence address onSaturday at 10:00 AM. However, because the supply-chain managementsystem operates just-in-time, the large items would be scheduled toarrive at a designated order aggregation facility at approximately 9:00AM Saturday instead of 5:00 PM Wednesday.

Based on this model, the inventory time for each item purchased by aconsumer is limited to the time elapsed since the item left the shippingfacility until the consumer received the item plus the inventory timeexperienced by the manufacturer or producer of the item.

In accordance with the shopping models described above, the inventorytime experienced by the manufacturers and producers can become veryshort due to the accurate consumption forecasts the supply-chainmanagement system can provide to the manufacturers and producers,whereby items are shipped as soon as they emerge from manufacturing.

D. Promotional Models

In a preferred embodiment, the promotion and introduction of new itemswill take place in window shops that provide merchants and consumerspromotional facilities and services that help merchants inform thepublic of their offerings and help consumers make selections anddecisions with respect to items they may be interested in acquiring.

From the consumer's perspective there are two distinct shoppingactivities. The first relates to purchasing an item the consumer haspurchased previously or with which the consumer is familiar, whereby thepurchase can be performed by a few clicks of the mouse. The secondrelates to purchasing an item the consumer has never purchased or anitem the consumer is not familiar with, whereby the purchase istypically preceded by an evaluation, comparison, and selection process.

The window shops address the second of these shopping activities asillustrated in the following example of a consumer interested in buyinga new HDTV to replace the old TV the family has used in the living roomfor 12 years. On a web browser, the consumer logs on to a web site thatlists all the window shops participating in the supply-chain managementsystem and searches for local window shops specializing in homeentertainment and HDTV. The web site preferably displays a window shoplocator with maps showing the locations of the various window shops thatspecialize in HDTV. The consumer selects a convenient location anddrives the family to the selected window shop where they can make aneducated decision on which HDTV they wish to purchase. The window shopsdo not have to carry inventory. Instead have space for displaying abroad selection of brands and models of items. They can provideinfomercial displays, video presentations describing the features andbenefits of the various brands and models, literature the consumers maywant to take home for further review and evaluation, and trainedtechnicians to assist consumers. Preferably, the technicians arequalified to answer consumer questions, explain item features, givedemonstrations, provide technical support and provide consumer training.In addition the window shops can have web browsers configured to supporta plurality of online shopping related activities for the use ofconsumers that visit the window shop. More specifically a consumer whoreaches a decision to purchase an item evaluated at the window shop canuse one of the web browsers at the window shop to make the purchase. Atthe same time the consumer can also purchase other items not related tothe window shop because window shops preferably participate in theintegrated inventory sharing sub-system and also operate asinventoryless retailers.

In a preferred embodiment of this model, the window shop providesmerchants promotional facilities and services that merchants can obtainunder contractual agreements for specified periods of time. The revenuemodel of the window shop is preferably based upon two sources. The firstrelates to service contracts with merchants to promote their products.The second relates to purchased orders placed by consumers that visitthe window shop.

Another function the window shop has a unique opportunity to perform isthe collection of information on consumers' interests and purchaseplans, which is of significant importance to manufacturers andproducers. During consumer visits to window shops, the window shoppersonnel have a unique opportunity to establish a friendly rapport withconsumers and a good justification to obtain from consumers extremelyvaluable information, which can include the following:

-   -   (a) An identification of each item a consumer may be interested        in acquiring.    -   (b) An identification of a date when a consumer may be        interested in buying each identified item.    -   (c) Contact information a consumer may be willing to provide.    -   (d) An identification of referrals a consumer may provide.

The collected information on consumers' interests and purchase plans canbe compiled and summarized in accordance with a standard format, wherebyit can be efficiently communicated to the manufacturers and producersthat provide the items for which the information is collected.

Another preferred embodiment of the promotion model consists of adecentralized exhibition system that offers merchants a network ofcollaborating window shops where merchants can promote and display theiritems to consumers, make new item introductions, and market test newitems. The decentralized exhibition system includes a database formaintaining data on each window shop in the network of window shops anda web server that merchants can access to negotiate contracts forpromotional services.

The decentralized exhibition system offers manufacturers and producersan excellent alternative to replace the conventional exhibitions halls.This alternative offers the following benefits:

-   -   1. The capability to reach a nationwide audience of consumers.    -   2. Year-round operation providing continuous exposure of items        to consumers.    -   3. Consumers can see the exhibitions at their convenience.    -   4. Window shops can be located in areas of high consumer traffic        to increase exposure of items to consumers.    -   5. Use can be targeted by geographic area.

The decentralized exhibition system is particularly suited forintroducing and market testing new items. For example, a manufacturercan contract for window shop promotional services from October throughDecember in New York, Denver, and Los Angeles, to market test a new itembefore committing to high volume production.

E. Retail Models

In a preferred embodiment, retailers will operate with minimum or noinventory to achieve significant cost savings in the operation of theirbusiness while providing their clientele improved item selection andservice. Retailers can use the integrated inventory sharing sub-systemto access inventory and can also rely on the continuous flow of itemsthrough the distribution pipeline to timely fulfill purchase orders fromconsumers.

Because of the very accurate consumption forecasts derived from thepredictive ordering shopping model described previously in Section A,manufactures and producers can plan just-in-time shipments to amultitude of regional distribution centers in accordance withanticipated consumption. These shipments will include the following twocategories:

items pre-sold to consumers through the predictive ordering sub-system,and

items expected to be sold based upon relatively accurate consumptionforecasts.

To accommodate the residual margin of error in the consumptionforecasts, the retailers in each regional area can maintain a smallvirtual inventory in a regional integrated inventory sharing sub-systemto ensure that orders from consumers can be promptly fulfilled. Withthis arrangement, the equivalent amount of shared inventory per retaileris equal to the small virtual inventory divided by the number ofretailers which should equate to an insignificant value.

The regional virtual inventory model offers a retailer the capability tofulfill purchase orders requiring immediate delivery irrespective of theitem ordered, the time the order is placed, the location of theconsumer, and the inventory held by the merchant.

If an order requires immediate delivery of a specific item, the virtualinventory model can identify a location having inventory of the item,which is closest to the consumer needing the item. Once the locationhaving inventory of the item is identified, the retailer can book theorder and the consumer has several alternatives to receive the item,including:

-   -   (1) Pick up the item at the identified location.    -   (2) Have the item sent to an order aggregation facility        proximate the consumer, where the consumer can pick up the item.    -   (3) Have the item delivered to an address specified by the        consumer.

This model addresses the issue of immediate delivery of online ordersand gives consumers the assurance of being able to instantly get anyitem at any time anywhere in the country.

On an average basis, it is expected that a consumer can buy an itemonline, drive to a designated place to pick up the item purchased anddrive back home in much less time than under the conventional system,which involves driving to a store, finding the item in the storeshelves, going through the checkout register and driving back home. Thiscomparison assumes that under the conventional system the consumer isable to find the item at the first store the consumer visits, whichoften is not the case and the consumer ends up by having to try severalstores before finding the needed item. The worst case under theconventional system happens when the item is not available anywhere inthe region, which forces the consumer to order the item from an out oftown merchant and wait a few days for delivery of the item.

The retail model also involves a potential reallocation of space in aretail establishment. Because of the inventory reduction, an appreciableamount of space may become available in a retail establishment.Depending upon the circumstances, the retailer can reallocate theavailable space to operate a shopping kiosk with shopping web browsers,a window shop, or an order aggregation facility, all of which wouldattract additional consumers to the retail establishment. For example,in a rural area a retailer may decide to operate a shopping kiosk and anorder aggregation facility to serve the residents of the rural area. Inanother example, a large box retailer in a downtown area may decide tooperate various window shops, each specializing in a different type ofitem. In still another example, a small retail establishment in ametropolitan area may decide to operate a shopping kiosk withcomfortable sitting and a coffee bar where patrons can enjoy a webshopping spree in a pleasant atmosphere.

F. Consumption Monitoring and Forecasting Models

Consumption monitoring and forecasting models are essential forimproving the productivity of manufactures and producers. The onlineshopping data collected in real-time by the supply-chain managementsystem can be compiled to provide each manufacturer or producer minuteby minute consumption data for each of the items the manufacturer orproducer provides. The consumption data can be analyzed to establishpotential correlations with factors that can affect consumption, such asweather conditions, season of the year, state of the economy, interestrates, etc. The consumption data can be further analyzed to establish acorrelation between consumption associated with predictive ordering andconsumption not associated with predictive ordering. These correlationsprovide the basis for generating accurate consumption forecasts for thebenefit of manufacturers and producers.

Another important correlation associated with real-time consumption datais consumption sensitivity to price. This can only be done withreal-time consumption data, whereby a manufacturer or producer canimplement a price change and get immediate feedback of the effect of theprice change on consumption. Once this correlation is established,manufacturers and producers will have the tools necessary to set pricesthat best fit their objectives. For example the price point can be setto satisfy one of a variety of different criteria. Examples of suchcriteria are optimization of revenue, profits, sales volume, salesvolume subject to given profit constraints, etc.

II. MAJOR COMPONENTS OF THE SUPPLY-CHAIN MANAGEMENT SYSTEM

FIG. 1 illustrates a block diagram of a preferred embodiment of thesupply-chain management system 100, which includes the following sixcomponents:

-   -   A. An order aggregation management sub-system 101.    -   B. An integrated inventory sharing sub-system 102.    -   C. A predictive ordering sub-system 103.    -   D. A consumer preference code sub-system 104.    -   E. A window shop management sub-system 105.    -   F. A supply-chain management sub-system 106.

The first five components are integrated together through supply-chainmanagement sub-system 106 as illustrated in FIG. 1 by interconnectinglines terminated by arrows between the components. Components 101-106can be considered as sub-systems of the supply-chain management system100 and an implementation may include these sub-systems as an integralpart of the supply-chain management system 100. For the purpose of thisdescription, the components 101-106 will be assumed to interact with asopposed to being part of the supply-chain management system 100 tobetter illustrate the functional aspects of each of the components.

In the sections that follow, each of the above components will bedescribed in further detail and further the description will explain theinterdependencies that may exist between the various components.

For ease of transaction tracking, preferably there are unique names forthe various participants and for the various transactions executed bythe participants in the supply-chain management system 100 that allowthe users to unambiguously look up and correlate information. Forparticipant names, technologies for effecting the uniqueness andcurrency of such names are well understood by those skilled in the art,and it is assumed that the supply-chain management system 100 enforces aunique naming scheme on all participants. For transactionidentification, each participant can label particular transactions withits own identification scheme, and the supply-chain management system100 can, for the convenience of all participants, provide a correlationservice, impose its own identification scheme, or both. Theseidentifications need to be communicated, preferably automatically, asorders are processed. This description assumes that such a technique forthe unambiguous identification of participants and transactions has beenemployed, and that transaction identifications are propagated throughthe system as transactions are processed.

A. The Order Aggregation Management Sub-system

The order aggregation management sub-system 101 provides the managementand coordination functions that support the concept of orderaggregation. This concept provides an efficient and cost effectiveweb-based system for managing the transfer of items from merchants toconsumers.

FIG. 2 shows a block diagram of a preferred embodiment of the orderaggregation management sub-system 101. The diagram includes anaggregation management database system 210, an order aggregation webserver 220, and a carrier management web server 230.

The order aggregation database system 210 is preferably organized by thetype of participant or transaction in the supply-chain management system100, in the following separate sections:

-   -   1. Merchant data 211 for each merchant participating in the        supply-chain management system 100, which can include:        -   (a) The identification of the merchant.        -   (b) The contact information for the merchant.        -   (c) The identification of shipping facilities from which the            merchant ships items purchased by consumers.        -   (d) The identification of a physical address of each of the            shipping facilities.    -   2. Purchase order data 212 for each consumer. When a consumer        places a purchase order with a merchant, a purchase order record        is preferably created in the aggregation management database        system 210, wherein for each purchase order record the purchase        order data for the consumer preferably includes the following:        -   (a) An identification of the consumer.        -   (b) An identification of the merchant.        -   (c) An identification of the purchase order.        -   (d) A time stamp identifying a booking date and time of the            purchase order.        -   (e) An identification of each of the items in the purchase            order.        -   (f) A quantity of each of the items in the purchase order.        -   (g) A price of each of the items listed in the purchase            order.    -   3. Aggregation and delivery data 213 for each purchase order        placed by consumer. Preferably, after the order is booked, the        consumer is given the opportunity to provide aggregation        instructions for the items purchased. The consumer can provide        the aggregation instructions after completing the purchase order        or after placing other purchase orders with other merchants,        which may take several days. The aggregation instructions can be        updated to include other purchases made by the consumer after        providing the aggregation instructions. Preferably when the        consumer books a new purchase order, the order aggregation        management sub-system 101, informs the consumer of any previous        pending orders placed by the consumer and not yet completed with        aggregation instructions. This gives the consumer the        opportunity to edit the aggregation instructions to include a        new purchase order in the aggregation instructions. The        aggregation and delivery data preferably includes the following:        -   (a) Consumer aggregation instructions for items designated            for physical aggregation in one or more purchase orders            placed by the consumer, wherein the consumer aggregation            instructions include combining the items designated for            physical aggregation listed in one or more purchase orders            in one or more batches, whereby the items in each batch are            physically aggregated together before being transferred to            the consumer.        -   (b) An identification of a date and time for the transfer of            each batch of physically aggregated items to the consumer.        -   (c) An identification of an order aggregation facility to            which the items in each batch are to be sent to be            physically aggregated.        -   (d) An identification of pick up and delivery information            for each batch of physically aggregated items, indicating            that the consumer will pick up the batch of physically            aggregated items at the identified order aggregation            facility or that the batch of physically aggregated items            will be delivered to an address designated by the consumer.    -   4. Order aggregation facility data 214 for each order        aggregation facility participating in the supply-chain        management system 100. The order aggregation facility data for        each order aggregation facility, preferably includes:        -   (a) The identification of the order aggregation facility.        -   (b) The contact information for the order aggregation            facility.        -   (c) The physical address of the order aggregation facility.        -   (d) Schedules of shipments to be received by the order            aggregation facility, which can be compiled from the            merchant data, the purchase order data, and the aggregation            and delivery data.        -   (e) A list of items included in each of the shipments, which            can be compiled from the merchant data, the purchase order            data, and the aggregation and delivery data.        -   (f) The identification of each consumer scheduled to receive            a physically aggregated batch of items from the order            aggregation facility, which can be extracted from the            aggregation and delivery data.        -   (g) Aggregation facility instructions, which can be compiled            from the merchant data, the purchase order data, and the            aggregation and delivery data, and include instructions for            temporarily storing the items scheduled to be received by            the order aggregation facility, instructions for aggregating            the items scheduled to be received by the order aggregation            facility; and instructions for transferring batches of            physically aggregated items to consumers.        -   (h) Aggregation facility schedules compliant with the            identified dates and times for transferring batches of            physically aggregated items to consumers, which can be            compiled from the aggregation and delivery data, and include            schedules for performing physical aggregations of items into            batches and schedules for transferring batches of physically            aggregated items to consumers.    -   5. Carrier data 215 for each of the carriers that provide        carrier services managed by the order aggregation management        sub-system, which can include:        -   (a) The identification of the carrier.        -   (b) The contact information for the carrier.        -   (c) An identification of the transportation resources used            by the carrier.        -   (d) An identification of the geographic areas and routes            serviced by the carrier.    -   6. Transportation data 216 consisting of carrier service        requests generated by the order aggregation management        sub-system in compliance with the aggregation and delivery data,        which preferably include:        -   (a) An identification of a point of origin.        -   (b) An identification of a point of destination.        -   (c) A listing of items to be carried.        -   (d) A transportation schedule.

The order aggregation web server 220 is preferably configured to accessthe aggregation management database system 210 and to executeapplication programs to coordinate the various tasks associated withtransfers of items from merchants to consumers. These applicationprograms can include the following:

-   -   1. A data entry and retrieval program 221 to enter and maintain        in real-time the aggregation management data in the aggregation        management database system and respond to queries related to the        aggregation management data.    -   2. A report generation program 222 for generating reports with        data and instructions for each order aggregation facility        participating in the operation of the order aggregation        management sub-system. This data can be extracted from the        merchant data, the purchase order data, and the aggregation and        delivery data.    -   3. An activity scheduling program 223 for scheduling activities        for each order aggregation facility, including the activities of        receiving, temporarily storing, physical aggregating, and        transferring to consumers items shipped to the order aggregation        facility.    -   4. A carrier service request generation program 224 configured        to schedule shipments of items designated for physical        aggregation. The program can use the aggregation and delivery        data to generate carrier service requests for each of the items        purchased by consumers to be transported from a point of origin        to the identified order aggregation facility in accordance with        a just-in-time schedule compliant with the aggregation and        delivery data.

The carrier management web server 230 is preferably configured to accessthe aggregation management database system 210 and to executeapplication programs to coordinate tasks associated with thetransportation operations of the plurality of carriers, based at leaston the data in the aggregation management database system. Theseapplication programs can include the following:

-   -   1. A service request management program 231 configured to        combine carrier service requests with the same point of origin,        the same point of destination, and the same transportation        schedule to optimize the utilization of the transportation        resources used by the carriers.    -   2. A carrier management program 232 configured to coordinate in        real-time the operation of the plurality of carriers that        provide carrier services to support the operation of the        supply-chain management system 100. Preferably, the carrier        coordination program 232 uses the transportation data stored in        the aggregation management database system to provide        coordination information that can be used by carrier services to        efficiently comply with carrier service requests to be        fulfilled.    -   3. A delivery scheduling program 233 for scheduling carrier        services to deliver batches of physically aggregated items to        consumers. For each delivery, the delivery scheduling program        233 can schedule a time for a delivery service to pick up a        batch of physically aggregated items for delivery to an address        designated by the consumer, at a designated date and time.        Preferably the program should be able to combine multiple        deliveries and pickups at consumer residences and order        aggregation facilities to optimize equipment utilization.

B. The Integrated Inventory Sharing Sub-System

The integrated inventory sharing sub-system 102 helps participatingmerchants reduce required operating inventories, balance inventories,reduce inventory costs, and fulfill consumer orders in the case of aninventory shortage. The system provides a Internet-based computingfoundation for participating merchants to share inventories. Eachparticipating merchant provides an inventory list of sharable items themerchant is willing to make available to the other merchantsparticipating in the inventory sharing sub-system. The composite of theinventory lists of sharable items provided by each of the merchantsrepresents a virtual inventory that is available to each of theparticipating merchants. Preferably, a merchant with an empty list ofsharable items can be a participant in the integrated inventory sharingsub-system and rely entirely on the virtual inventory to run a retailbusiness. Assuming participation from most merchants, the integratedinventory sharing sub-system creates an open market for the inventory inthe distribution pipeline, which allows the inventory to be available,in real-time, wherever the demand exists. For example, the integratedinventory sharing sub-system may be used to locate an item in closeproximity to the place where the item is needed.

FIG. 3 shows a block diagram of a preferred embodiment of the integratedinventory sharing sub-system 102. The Internet-based computingfoundation of the integrated inventory sharing sub-system 102 preferablyincludes an inventory sharing database system 310 configured to storeinventory sharing data and a virtual inventory web server 320 configuredto access the inventory sharing data database system 310 and to executeapplication programs to operate the integrated inventory sharingsub-system 102.

The inventory sharing database system 310 is preferably configured toinclude the following information:

-   -   1. Merchant sharing data 311 for each participating merchant        including merchants that do not hold inventory. Preferably, the        merchant sharing data includes the following:        -   (a) An identification of the merchant.        -   (b) An identification of sharable inventory data consisting            of:            -   (1) An identification of sharable items, wherein a                sharable item is an item the merchant is willing to make                available to the other merchants.            -   (2) A quantity associated with each sharable item.            -   (3) A physical location of each sharable item.        -   (c) Bid and ask prices and quantities for each of the items            the merchant may acquire from other merchants or provide to            other merchants.    -   2. Virtual inventory data 312 obtained by computing a composite        of the sharable inventory data of all the merchants        participating in the integrated inventory sharing sub-system.

The virtual inventory web server 320 is preferably configured to accessthe inventory sharing database system 310 and to execute applicationprograms to operate the integrated inventory sharing sub-system 102.These programs preferably include:

-   -   1. A data entry and retrieval program 321 configured to enter        and maintain the inventory sharing data in real-time in the        inventory sharing database system and respond to queries related        to the inventory sharing data.    -   2. A maintenance program 322 configured update the virtual        inventory data in real-time upon a change of the sharable        inventory data of a merchant. Such program needs to be able        detect any changes in the sharable inventory data of each        merchant participating in the integrated inventory sharing        sub-system. Upon detecting a change, the program needs to update        the computation of the virtual inventory.    -   3. A query program 323 configured to respond to queries related        to the virtual inventory in real-time. Merchants can use this        program to access the virtual inventory when contemplating        transactions related to the virtual inventory. For example a        merchant with insufficient inventory to complete the fulfillment        of a purchase order, may query the virtual inventory to identify        a merchant having the items needed. In another example a        merchant with surplus inventory of a particular item may post a        competitive price on the surplus item to encourage other        merchants to use the surplus or to trigger a transaction to        transfer the surplus inventory to another merchant able to use        the surplus inventory.    -   4. A transaction processing program 324 configured to execute        transactions between merchants, whereby each merchant can use        the transaction processing program to negotiate and perform an        inventory transaction with another merchant based at least on        the virtual inventory data. Preferably the transaction        processing program supports inventory transactions between        merchants whereby one merchant can acquire inventory from        another merchant and pay the other merchant for the acquired        inventory.    -   5. A market making program 325 configured to match bid prices        and quantities provided by each merchant with ask prices and        quantities provided by each other merchant, based at least on        the merchant sharing data. This program can facilitate the        process by which a merchant can identify other merchants with        which to execute a particular inventory transaction.

C. The Predictive Ordering Consumption Forecasting Sub-System

The predictive ordering Consumption Forecasting sub-system 103constitutes the implementation of the predictive ordering shopping modeldescribed in section I.A. In a preferred embodiment of the predictiveordering sub-system 103, a consumer is given a predictive price discountin exchange for placing a predictive purchase order for an item with amerchant at an order date and accepting delivery at a later deliverydate. For the purposes of this description, a predictive order delay(POD) is a time span between the predictive purchase order date and thedelivery date. The predictive price discount depends upon the POD and isbased upon a cost savings realized by the supply-chain as a result ofthe advanced knowledge of the predictive purchase order. Preferably,predictive purchase orders are propagated in real-time up thesupply-chain to the source manufacturers and producers of the itemsordered through the predictive ordering sub-system 103. Historicalinformation on predictive purchase orders can be compared withhistorical information on non-predictive purchase orders for identicalperiods of time to establish a correlation factor between predictive andnon-predictive purchase orders. The correlation factor can be applied topredictive purchase orders to derive accurate projections of futureconsumption. Accurate consumption forecasts can provide a powerful toolfor the supply-chain to achieve significant productivity improvements.Typically, the major productivity improvements are experienced by sourcemanufacturers, producers, and service providers. The achievableproductivity improvements will depend upon how far in the future theforecasts can provide reliable information which depends upon thepredictive order delay (POD) and the manufacturing or production cycleassociated with each item. For example, for an item with a manufacturingcycle of one week a predictive purchase order for delivery two weekslater may represent very valuable information. Each manufacturer andproducer should be able to compute the cost savings attributable toaccurate consumption forecasts and determine the portion of such costsavings that can be passed on to consumers in the form of predictiveprice discounts. The effect of the predictive order delay (POD) upon thecost savings can be computed to provide the basis for predictivediscount schedules of predictive price discount versus predictive orderdelay.

FIG. 4 shows a block diagram of a preferred embodiment of the predictiveordering sub-system 103. Preferably, the predictive ordering sub-system103 includes a predictive ordering database system 410 and a predictiveordering web server 420 configured to access the predictive orderingdatabase system 410 and to execute application programs to operate thepredictive ordering sub-system 103.

The predictive ordering data database system 410 is preferably organizedin the following sections:

Cost saving data 411 for each of the items subject to the predictiveprice discount, which can include:

-   -   1. An identification of the item.    -   2. A matrix of estimated cost savings versus predictive order        delay and predictive order volume.

Predictive discount data 412 for each of the merchants participating inthe predictive ordering sub-system 103, which can include:

-   -   1. An identification of the merchant.    -   2. An identification of the items supplied by the merchant        subject to the predictive price discount.    -   3. An identification of a predictive discount schedule for each        of the items subject to the predictive price discount, wherein        the predictive discount schedule identifies the predictive price        discount versus the predictive order delay. In a preferred        embodiment, the price discount, expressed as a percentage of the        regular price listed by the merchant, is uniform across all        merchants. Because the list price may vary from merchant to        merchant, the absolute value of the discount is proportional to        the list price. Different embodiments may apply other discount        rules. For example an embodiment may allow each participating        merchant to determine its own predictive discount schedule.

Real consumption data 413 for each of the items subject to thepredictive price discount, which can include:

-   -   1. An identification of the item.    -   2. The actual consumption of the item compiled from delivered        purchase orders for the item. Preferably, the consumption data        is configured to provide reports based on a variety of criteria        such as by time period, geographic region, retailer booking the        order, etc.

Forecasted consumption data 414 for each of the items subject to thepredictive ordering sub-system 103, which can include:

-   -   1. An identification of the item.    -   2. The forecasted consumption of the item based upon predictive        purchase orders booked, analyzed real consumption data, and        historical correlations between predictive and non-predictive        purchase orders booked. Preferably, the forecasted consumption        data is configured to provide reports based on a variety of        criteria such as by time period, geographic region, retailer        booking the order, etc.

The predictive ordering web server 420 is preferably configured toaccess the predictive ordering data database system 410 and to executeapplication programs to support the operation of the predictive orderingsub-system 103. These programs preferably include:

-   -   1. A data entry and retrieval program 421 configured to enter        and maintain predictive ordering data in the predictive ordering        database sub-system 410 and respond to queries related to        predictive ordering data.    -   2. A cost savings program 422 configured to estimate, for each        of the items subject to the predictive price discount, a cost        savings realized by the supply-chain versus the predictive order        delay. This program preferably receives as input certain        parameters that identify and quantify the impact of the advanced        knowledge of the purchase or order on the cost savings.    -   3. A real consumption monitoring program 423 configured to        analyze real consumption data.    -   4. A consumption forecasting program 424 configured to generate        consumption forecasts based upon predictive purchase orders        booked, analyzed real consumption data, and identified        correlation factors between predictive and non-predictive        purchase orders booked.

D. The Consumer Preference Code Sub-System

The consumer preference code sub-system 104 constitutes oneimplementation of the consumer preference codes shopping model describedin section I.A. The consumer preference code sub-system 104 provides asystematic solution for the problem of identifying items of non-uniformtype that meet the preferences of a consumer. The consumer preferencecode sub-system 104 identifies for each class of non-uniform genericitems known by consumers by a generic name, a plurality of sub-classeswherein the items in each sub-class are representative of a differentconsumer preference. Using the consumer preference code sub-system 104,a consumer can place an order online for an item of non-uniform typewith confidence that the item ordered will conform to the preferences ofthe consumer.

FIG. 5 shows a block diagram of a preferred embodiment of the consumerpreference code sub-system 104. Preferably, the consumer preference codesub-system 104 includes a preference code database system 510 configuredto store preference code data and a preference code web server 520configured to access the preference code database system 510 and toexecute application programs to operate the consumer preference codesub-system 104.

The preference code database system 510 is preferably configured tostore preference code data for each class of non-uniform generic itemsof a plurality of different classes of non-uniform generic itemsidentified by a generic name. The preference code data can be organizedin the following three categories:

-   -   1. Class data 511, wherein the class data 511 can include an        identification of the class of non-uniform generic items and an        association of the class of non-uniform generic items with the        generic name.    -   2. Sub-class data 512 for each class of non-uniform generic        items, wherein each sub-class represents a different consumer        preference. For each class, the sub-class data 512 preferably        includes:        -   (a) An identification of each characteristic of a set of            quantifiable characteristics used to define the sub-class.            Preferably, the identification of each quantifiable            characteristic is represented by at least one word            describing the quantifiable characteristic.        -   (b) An identification of a range of values for each            characteristic of the set of identified quantifiable            characteristics, wherein each of the values in the range            represents a measure of the quantifiable characteristic.        -   (c) An identification of the sub-class. The identification            of the sub-class can include the generic name of the items            in the class and an assigned value for each of the            quantifiable characteristics used to define the sub-class.    -   3. Consumer data 513 for each consumer of a plurality of        consumers that subscribe to the consumer preference code        sub-system. For each consumer, the consumer data 513 for each        consumer preference preferably includes:        -   (a) An identification of the consumer.        -   (b) An identification of a class of non-uniform generic            items        -   (c) An identification of a sub-class identified by the            consumer as representing a preference of the consumer.        -   (d) An identification of an optional personalized reference            supplied by the consumer for the sub-class identified by the            consumer as representing a preference of the consumer. The            personalized reference can be used as shorthand to designate            the sub-class and should be associated with the class of            non-uniform generic items from which the sub-class is            derived, the sub-class, and the consumer.

The preference code web server 520 is preferably configured to accessthe preference code database system 510 and to execute applicationprograms to operate the consumer preference code sub-system 104. Theseprograms preferably include:

-   -   1. A data entry and retrieval program 521 configured to enter        and maintain the preference code data in the preference code        database system 510 and respond to queries related to the        preference code data.    -   2. A personalized reference program 522 configured to receive as        input the identification of a consumer and the identification of        a generic name associated with a class of non-uniform generic        items. Based on the input the program returns each of the        optional personalized references supplied by the consumer for        the class of non-uniform generic items associated with the        generic name. When a consumer shops online for a generic item,        once the generic item is selected by the consumer the        personalized reference program can automatically display the        personal references the consumer created. Then the consumer can        just click on the desired personalized reference to complete the        selection.    -   3. A consumer preference subscription program 523 configured to        display on a browser web pages for a consumer to subscribe to        the consumer preference code sub-system. Preferably, the program        will include the following components:        -   (a) A component for the consumer to register as a user of            the consumer preference code sub-system.        -   (b) A component for the consumer to select a class of            non-uniform generic items.        -   (c) A component for the consumer to select a sub-class of            generic items from the class of non-uniform generic items.        -   (d) A component for the consumer to register a preference            for the selected sub-class.        -   (e) A component for the consumer to provide an optional            personalized reference the consumer may wish use to refer to            the sub-class of generic items.

E. The Window Shop Management Sub-System

With the deployment of the supply-chain management system 100, theconventional retail stores that operate as very costly warehouses withshelves full of merchandise will tend to disappear because they operateunder a most inefficient business model. However, these inefficientretail stores have fulfilled an important social need commonly known as“window shopping” that will remain and should not be avoided. With thesupply-chain management system 100, the window shop provides a new modelto fulfill the “window shopping” social need. This new model addressesthe “window shopping” need with a direct approach that focuses on thebasic reason that drives consumers to window shop. That basic reason isdriven by consumers needing to justify to themselves their own buyingimpulses. The window shop is especially configured to provide consumersall the justification they need to eventually make that buying decisionand feel very good about it.

The window shop management sub-system 105 constitutes one implementationof the promotion and introduction models described earlier in sectionI.D. The window shop management sub-system 105 manages and coordinatesthe operation of a plurality of window shops, wherein a window shop is acommercial establishment configured to provide display space andfacilities where merchants can display, promote, present, and launchtheir items. Preferably, each window shop is staffed with personnelqualified to explain item features, give demonstrations, answer consumerinquiries, provide technical support, provide consumer training, andassist consumers with selection of items and order placement. In thewindow shop consumers can make informed selections and decisions withrespect to items they may be interested in acquiring.

Preferably, the window shop management sub-system 105 also performs thefunction of compiling and summarizing information on consumers'interests and purchase plans collected by window shop personnel duringconsumer visits to window shops as indicated in Section I.D. Thecompiled and summarized information is preferably communicated by thewindow shop management sub-system to the manufacturers and producersthat provide the items for which the information is collected.

The window shop management sub-system 105 also coordinates and operatesthe decentralized exhibition system as a general promotional andadvertising service offered to manufacturers and service providers topromote and advertise their items. The decentralized exhibition systemgives manufacturers and service providers the opportunity to appeal tothe consumer's desire for novelty, performance, quality, and pride ofownership without exerting undesirable pressure tactics that consumersoften resent. The decentralized exhibition system can become aneffective and compelling alternative to the conventional promotional andadvertising models often based on misleading information, brute force,and shot gun tactics to attract consumers.

FIG. 6 shows a block diagram of a preferred embodiment of the windowshop management sub-system 105 that manages a plurality of window shops601 and manages a decentralized exhibition system not shown in thefigure. Preferably, the window shop management sub-system 105 includes awindow shop database system 611 configured to store window shop data foreach of the participating window shops and a window shop web server 621configured to access the window shop database system 611 and to executeapplication programs to coordinate tasks associated with the operationof the plurality of window shops 601 and the decentralized exhibitionsystem. In addition, the window shop management sub-system 105 can alsouse a web server running an online shopping platform 631 and an onlineorder booking platform 632, both of which can be provided by thesupply-chain management sub-system 106.

The window shop database system 611 is preferably configured to storewindow shop data, wherein the window shop data for each window shop of aplurality of window shops supervised by the window shop managementsub-system preferably includes the following:

-   -   1. An identification of the window shop.    -   2. An identification of contact information for the window shop.    -   3. An identification of the physical location and address of the        window shop.    -   4. A description of facilities and services provided by the        window shop.    -   5. An identification of days and hours of operation for the        services offered by the window shop.    -   6. An identification of each item promoted by the window shop on        the behalf of merchants that book the services of the window        shop. Preferably the identification of each item is maintained        in real-time, whereby the window shop web server can respond to        a query inquiring which window shops promote a given item.    -   7. An identification of terms, conditions, and fees applicable        to the facilities and services provided by the window shop to        merchants.    -   8. An availability record identifying the availability of        facilities and services provided by the window shop versus        calendar time. Using the availability record, the window shop        can respond to availability inquiries for the facilities and        services provided by the window shop.

Preferably, window shops maintain historical records of services andfacilities provided to merchants. These records can provide veryvaluable information for the study and analysis of the relativeeffectiveness of the window shop model as a promotion and advertisingtool.

The window shop web server 621 is preferably configured to access thewindow shop database system 611 and to execute application programs tocoordinate tasks associated with the operation of each window shop andthe decentralized exhibition system. These application programs caninclude the following:

-   -   1. A data entry and retrieval program 622, configured to enter        and maintain the window shop data in the window shop database        system 611 and respond to queries related to each of window        shops.    -   2. A web-based promotion and advertising program 623, configured        to promote and advertise to merchants the facilities and        services a window shop provides for the benefit of merchants.    -   3. A browsing program 624, configured to provide browsing web        pages to view and browse window shop data.    -   4. A matching program 625 configured to match a given set of        merchant requirements for window shop facilities and services        with each window shop configured to fulfill the given set of        merchant requirements.    -   5. A window shop reservation program 626, configured to reserve        window shop facilities and services during a given period of        time in one or more geographic locations. The reservation        program can be used in connection with the decentralized        exhibition system for market testing of new items, new item        launches, focus groups, etc.    -   6. A window shop brokerage program 627, configured to execute        booking transactions between merchants and window shops for        facilities and services provided by window shops.    -   7. A window shop locator program 628, configured to locate        window shops based on given criteria, wherein the given criteria        include the identification of item represented by a window shop        and a distance from a specified location to the window shop.

The web server running the online shopping platform 631 is preferablyconfigured to support consumer online shopping and interface with thesupply-chain management sub-system 106. The window shops are preferablyequipped with browsers for the use of consumers who wish to access theonline shopping platform while visiting the window shop. For theconvenience of window shops wishing to offer online shopping toconsumers, the supply-chain management sub-system 106 can be configuredto provide these web servers that display web pages for supporting aplurality of online shopping related activities.

The web server running the online order booking platform 632 ispreferably configured to support order booking and processing servicesfor booking and processing purchase orders placed by consumers. Theonline order booking platform 632 can be accessed by the window shoppersonnel and is preferably configured to interface with thesupply-chain management sub-system 106. For the convenience ofmerchants, the supply-chain management sub-system 106 can be configuredto provide web servers that offer order booking services for each of thewindow shops wishing to use the services.

From a functional perspective a window shop serves two distinctfunctions in one facility. A first function provides window shopservices for manufacturers, producers, service providers, and consumers.A second function operates in the capacity of a retailer that sellsitems to consumers. This dual function creates a favorable synergy withthe potential of making a window shop a very successful business model.

F. The Supply-Chain Management Sub-System

FIG. 7 shows a block diagram illustrating a preferred embodiment of thesupply-chain management sub-system 106. As previously shown in FIG. 1,to support the just-in-time operation of the supply-chain managementsystem 100, the supply-chain management sub-system 106 can be configuredto integrate and provide coordination for the operation of the followingsub-system components shown separately in FIG. 7 and previouslydescribed in Sections II.A-E:

-   -   (A) The order aggregation management sub-system 101, to        facilitate a rapid transfer of items from merchants to consumers        and reduce transportation costs in the supply-chain.    -   (B) The integrated inventory sharing sub-system 102, to help        reduce inventories held by merchants.    -   (C) The predictive ordering sub-system 103, to provide accurate        forecasting of future consumption.    -   (D) The consumer preference code sub-system 104, to facilitate        online shopping of non-uniform generic items.    -   (E) The window shop management sub-system 105, to manage window        shops where consumers can fulfill their window shopping needs        and where manufacturers and producers can promote or launch new        items.

In addition, the supply-chain management sub-system 100 can perform thefollowing functions:

-   -   (a) Track inventory levels in the supply-chain and reduce        inventory levels in the supply-chain.    -   (b) Collect consumption data in real-time and distribute        consumption data in real-time to manufactures and producers to        improve manufacturing and production efficiency.    -   (c) Integrate and coordinate the operation of a set of        Internet-based transaction platforms and tools that facilitate        online shopping, predict and stabilize consumption, reduce        overall supply-chain costs, and promote economic growth.

To emphasize the multiplicity of functional aspects of this inventionthis description addresses a configuration where the five sub-systemcomponents (A) through (E) listed above operate as sub-systems of thesupply-chain management system 100. More specifically, FIGS. 2-6 includeseparate references to various boxes representing database systems andvarious boxes representing data, whereby some of the database systemsand data represented in the different figures may physically be thesame. For example, FIG. 2 shows merchant data 211 and FIG. 3 showsmerchant sharing data 311 because theoretically the set of merchantsthat participate in the order aggregation management sub-system 101 maynot be the same as the set of merchants that participate in theintegrated inventory sharing sub-system 102. For these reasons FIG. 7also includes the sub-system blocks 101 through 105, which are the othersub-components of the supply-chain management system 100. However, animplementation may choose to integrate these sub-components into acomplex supply-chain management system that includes all the functionsrelated to blocks 101 through 106. In another example, FIGS. 6 and 7refer to web servers running online shopping platforms and web serversrunning online order booking platforms to emphasize the differences inthe functional aspects of order placement and order booking. However, animplementation may choose to combine these two functions in one server,which is the conventional approach for online shopping.

FIG. 7 also depicts the following basic components of the supply-chainmanagement sub-system 106:

-   -   1. Inventory management database systems 701 which can be        configured to store merchant inventory data in real-time for        each merchant participating in the supply-chain management        system as transactions that affect inventories take place.    -   2. Order history database systems 702 preferably configured to        store booked order data for each purchase order booked by each        merchant participating in the supply-chain management system.    -   3. Item information database systems 703 preferably configured        to store item data for each item provided by at least one        merchant of the plurality of merchants participating in the        supply-chain management system, wherein the item data        characterizes the item.    -   4. Web servers running online shopping platforms 711 which can        be configured to provide web pages for supporting a plurality of        online shopping activities that facilitate online shopping by        consumers from merchants in accordance with the requirements of        the supply-chain management system 100.    -   5. Web servers running online order booking platforms 712 which        can be configured to provide merchants with online order booking        services compliant with the requirements of the supply-chain        management system 100.    -   6. Web servers running real-time consumption monitoring        platforms 713 which can be configured to execute programs to        compile consumption monitoring data in real-time for each item        provided by the merchants participating in the supply-chain        management system based at least on purchase orders booked and        to provide consumption data and consumption forecasts.    -   7. Web servers running real-time financial transaction        integrated systems 714 which can be configured to execute        financial transactions among entities participating in the        supply-chain management system 100 to reduce execution times and        costs associated with the financial transactions.

For merchants that already use modern computer-based systems configuredto manage and update inventories in real-time, support online shopping,support online order booking, and execute financial transactions online,the supply-chain management sub-system 106 can provide integration toolsto integrate such modern computer-based systems into the supply-chainmanagement sub-system 106.

The inventory management database systems 701, are preferably configuredto store inventory data for each merchant, which can include:

-   -   (a) An identification of the merchant.    -   (b) An identification of each different item of the items held        in inventory by the merchant.    -   (c) An inventory quantity associated with each different item of        the items held in inventory by the merchant.    -   (d) An available quantity associated with each different item of        the items held in inventory by the merchant. The available        quantity represents the quantity of the item that is available        for sale to consumers and corresponds to the quantity in        inventory minus a quantity that may have been placed on        reservation for pending transactions.    -   (e) A reserved quantity associated with each different item of        the items held in inventory by the merchant. The reserved        quantity represents the quantity of the item that is placed on        temporary reservation in response to requests for quotations        from consumers. When a consumer submits to the merchant a        request for a quotation for a given quantity of an item, that        quantity of the item is temporality removed from the available        quantity and added to the reserved quantity to give the consumer        the opportunity to complete an order for the purchase of the        item from the merchant with assurance that the order can be        fulfilled.    -   (f) A historical record of items received, manufactured, or        produced by each merchant. For each different item received,        manufactured, or produced by a merchant, the historical record        preferably includes the date and quantity associated with the        receipt, manufacture, or production of the item.

The order history database systems 702, preferably store order data foreach order booked, which includes:

-   -   (a) Purchase order data 212 initially stored in the aggregation        management database system 210.    -   (b) Aggregation and delivery data 213 initially stored in the        aggregation management database system 210.    -   (c) Data collected in connection with the order from the booking        step to the delivery step.

It should be understood that the configuration of the order historydatabase systems 702 described above is merely illustrative of thefunctional aspects of the supply-chain management sub-system 106 andthat an implementation may choose a configuration based upon efficiencyand/or other considerations.

The item information database systems 703, are preferably used to storedescriptive information for the items provided by the merchantsparticipating in the supply-chain management system 100 and provides thefoundation for the creation of a universal catalog of items (productsand services) described later in this section.

The general purpose web servers running online shopping platforms 711are preferably configured to provide web pages for supporting aplurality of consumer online shopping activities normally performed byconsumers such as:

-   -   (a) Item selection among the items provided by the merchants        that subscribe to the supply-chain management system 100.    -   (b) Obtaining pricing and availability information.    -   (c) Order placement.    -   (d) Entry of delivery information the consumer may specify.    -   (e) Entry of order aggregation instructions when the consumer        whishes to receive, from an order aggregation facility,        described previously in Section I.C, at least one of the items        ordered from different merchants.    -   (f) Order entry.    -   (g) Payment execution.

In a preferred embodiment, the supply-chain management sub-system 106provides user friendly shopping platforms to encourage consumers toconvert to the comfort of online shopping. The rapid growth of onlineshopping in recent years shows concrete evidence of the acceptance ofonline shopping by consumers. However, in its present form, onlineshopping still suffers from a number of disadvantages and inconvenienceswell know to consumers, which include shipping charges, shipping time,delivery problems, inability to ascertain if the items ordered onlinemeet the consumer's expectations, inability to obtain a desired item onshort notice, etc. These disadvantages and inconveniences are eliminatedby the supply-chain management system 100, thereby opening the door foronline shopping to become the prevailing model by which consumers shop.

A consumer can setup a personal account in the supply-chain managementsub-system 106, whereby online shopping becomes a very simple process.The consumer logs-in a personal account, clicks on the desired items andquantities, clicks on a default pick up and delivery information orenters a different one, and completes the shopping by clicking on anapproval button. There is no need to enter payment information becausethe payment can be set to an automatic mode. There is no need to enterpick up and delivery information if the consumer has already entered onein connection with other previous purchases. Preferably the onlineshopping platforms can be accessed from the consumer's home computer orfrom browsers expected to be available is most commercialestablishments.

The general purpose web servers running online order booking platforms712 are preferably configured to provide order booking services formerchants that participate in the supply-chain management system 100. Tosupport the real-time operation of the supply-chain management system100, the order booking platforms 712 preferably communicate in real-timewith the online shopping platforms and the inventory management databasesystems 701 to update inventories as purchase orders are booked. Theorder booking data can be directed to the order aggregation managementsub-system 101 for further processing and subsequently the orderinformation can be stored in the order history database systems 702.

The order booking platforms 712 are intended for the use of merchantsthat do not have modern computer-based systems to book orders online inreal-time. For the merchants that already use such modern computer-basedsystems, the supply-chain management sub-system 106 can provideintegration tools to integrate such modern computer-based systems intothe supply-chain management sub-system 106.

In a preferred embodiment of the order booking platforms 712, the orderbooking services include:

-   -   (a) A request for quotation component configured to receive from        a consumer a request for quotation in the form of a list of one        or more items and an identified quantity for each of the items        on the list.    -   (b) A quotation component configured to respond to the request        for quotation by providing to the consumer, for each item on the        list, a quotation taking into consideration the identified        quantity of the item and further indicating for each item on the        list the quantity available in inventory when the identified        quantity exceeds the quantity available in inventory. The        quotation component can be configured to support predictive        ordering.    -   (c) A reservation component, including the steps of placing a        quantity of each item on the list on temporary reservation on        the behalf of the consumer and providing the consumer a        confirmation of the temporary reservation indicating the        quantity of each item on the list placed on temporary        reservation on the behalf of the consumer. For the purposes of        this step, the quantity placed on temporary reservation can be        the lesser of the requested quantity and the quantity available        in inventory.    -   (d) A booking component configured to receive from a consumer a        purchase order in the form of a list of one or more items and an        identified quantity for each of the items on the list.    -   (e) An order processing component configured to perform order        processing tasks for each of the items listed in the purchase        order. Preferably the order processing tasks include:        -   1. Updating the inventory held by the merchant by            subtracting the identified quantity associated with the item            from the quantity of the item held inventory by the            merchant.        -   2. Terminating a temporary reservation that may have been            placed on the quantity of the item in connection with the            request for quotation related to the purchase order.        -   3. Designating the identified quantity of the item as sold            to the consumer.        -   4. Planning the generation of inventory to fulfill            predictive purchase orders booked for future delivery.    -   (f) A component for receipt of delivery information the consumer        may wish specify.    -   (g) A component for receipt of order aggregation instructions        when the consumer whishes to receive, from an order aggregation        facility, at least one item ordered from a merchant.    -   (h) A component for receipt of payment.

The web servers running online shopping platforms for consumers to shopand the web servers running online order booking platforms for merchantsto book orders from consumers have been described separately for thepurpose of distinguishing the two distinct functions performed by theseservers. The first serves the consumer whereas the second serves themerchant. However an implementation may choose to combine the twofunctions in one server since the two functions are deeply interrelated.

The web servers running real-time consumption monitoring platforms 713are preferably configured to execute programs to collect and compileconsumption monitoring data in real-time and generate consumptionforecasts for each of a plurality of items provided by the merchantsparticipating in the supply-chain management system based at least onpurchase orders received by each of the merchants from consumers.Preferably, consumption monitoring data for each item includes thefollowing components:

-   -   (a) For each merchant, a merchant specific consumption rate over        each of an identified set of time segments. For each of the time        segments the merchant specific consumption rate over the time        segment represents the total quantity of the item booked by the        merchant during the time segment.    -   (b) A global consumption rate over each of an identified set of        time segments. For each of the time segments the global        consumption rate over the time segment represents the summation        of the merchant specific consumption rates of each merchant        during the time segment.    -   (c) For each merchant, a merchant specific predictive        consumption rate over each of an identified set of future time        segments. For each of the future time segments, the merchant        specific predictive consumption rate over the future time        segment represents the total quantity of the item, booked by the        merchant using the predictive ordering sub-system 103 that is        scheduled for delivery during the future time segment.    -   (d) A global predictive consumption rate over each of an        identified set of future time segments. For each of the        identified set of future time segments the global predictive        consumption rate over the future time segment represents the        summation of the merchant specific predictive consumption rates        of each merchant over the future time segment.

The above consumption rates can be used to generate accurate consumptionforecasts for each of a plurality of items provided by the merchantsparticipating in the supply-chain management system. These consumptionrates can be used by merchants and in particular by manufacturers andproducers to improve productivity.

The web servers running real-time financial transaction integratedsystems 714 are preferably configured to facilitate financialtransactions among the entities participating in the supply-chainmanagement system 100 to reduce execution times and costs associatedwith the financial transactions.

For example, when a merchant acquires inventory from another merchantbased on the integrated inventory sharing sub-system 102, the financialtransaction integrated system 714 can execute an automatic financialtransaction to pay for the acquired inventory as previously mentioned inSection II.B. Once the inventory is legally transferred to the merchantacquiring the inventory, the financial transaction integrated system 714can automatically transfer from an identified bank account of themerchant acquiring the inventory to an identified bank account of themerchant providing the inventory an identified amount representing thepayment for the inventory transferred.

In another example, a consumer can register an automatic method ofpayment with the supply-chain management sub-system whereby eachpurchase made by the consumer is automatically charged to a paymentsystem designated by the consumer.

The financial transaction integrated systems 714 can be used bymerchants that do not have modern computer-based systems configured toexecute financial transactions in real-time. For the merchants thatalready use such modern computer-based systems, the supply-chainmanagement sub-system 106 can provide integration tools to integratesuch modern computer-based systems into the supply-chain managementsub-system 106.

For financial transactions between merchants, the financial transactionintegrated systems 714 can include the following components:

-   -   (a) A financial transaction database system configured to store        and maintain financial transaction data related to financial        transactions among the plurality of merchants. For each        merchant, the financial transaction data can include:        -   1. An identification of a bank account established by the            merchant with a banking institution, wherein the bank            account can be used to execute automatic financial            transactions between the merchant and other merchants.        -   2. Terms and conditions imposed by the merchant for            execution of automatic financial transactions between the            merchant and other merchants.    -   (b) An automated financial transaction execution system that        automatically associates each financial transaction among        merchants with the merchants participating in the transaction        and automatically executes transfers of funds between the        identified bank accounts of the merchants associated with the        financial transaction in accordance with terms and conditions        imposed by the merchants participating in the financial        transaction.

For financial transactions between merchants and consumers, conventionalelectronic financial transaction systems can be used. These systems arewell understood by those skilled in the art and will not be furtherdescribed.

The supply-chain management sub-system can also provide severalimportant by-products that facilitate the interactions between al theparticipants in the supply-chain management system 100. Theseby-products include the following:

-   -   (1) A universal directory of merchants that participate in the        supply-chain management system. This directory can be derived        from merchant data stored in the database systems that support        the supply-chain management system. Although FIG. 2 refers to        merchant data 211 and FIG. 3 refers to merchant data 311 to        emphasize the distinct functionalities of these two sub-systems,        a preferred embodiment could use a single database to store        merchant data and avoid duplications. The universal directory        can be configured with a search utility that provides        flexibility for a variety of search criteria such as by merchant        name, by merchant location, by type of item (product or service)        provided by the merchant, etc.    -   (2) A universal directory of original manufacturers, producers,        and service providers. This directory would represent a subset        of the universal directory of merchants since all the entries        would also be merchants. In this case the search criteria can        also include search by specific item (product or service).    -   (3) A universal directory of retailers. This directory would        also represent a subset of the universal directory of merchants        and the search criteria can also include search by region, by        type of items retailed, etc.    -   (4) A universal catalog of items (products or services) listing        each of the different items provided by the merchants        participating in the supply-chain management system. This        catalog can be configured with a search utility that provides        flexibility for a variety of search criteria such as by brand,        by original manufacturer, producer, or service provider, by item        type, by item name, by the UPC code of the item etc.

The universal directories and the universal catalog of items can becomepowerful tools to facilitate and improve the activities of allparticipants in the supply-chain from original manufacturers andproducers of the items to the consumers that consume the items.

III. OPERATION OF THE SUPPLY-CHAIN MANAGEMENT SYSTEM

Section II described six basic sub-system components that are integratedto support the operation of the supply-chain management system 100. Thissection further introduces seven physical elements that are an integralpart of the operation of the supply-chain management system anddescribes the methods of operation of the supply-chain management systemin connection with the six basic sub-system components and the sevenphysical elements, in a preferred embodiment of the invention.

FIG. 8 illustrates a block diagram 800 depicting the six basicsub-system components of the supply-chain management system, shown inFIG. 1, the seven physical elements that are an integral part of thesupply-chain with a double border, and important inter-operative linksbetween the sub-system components and the seven physical elements. Theseven physical elements depicted in FIG. 8 are:

-   -   A. Manufacturers and producers 801, representing the starting        point of the supply-chain.    -   B. Carrier Services 802, which physically move items along the        supply-chain.    -   C. Distribution centers 803, which provide intermediate transfer        points along the supply-chain to improve transportation        efficiency.    -   D. Order aggregation facilities 804, which provide the final        transfer point from where aggregated orders are cost effectively        transferred to consumers.    -   E. Retailers 805, which provide the functions of offering items        to consumers and booking purchase orders from consumers.    -   F. Window shops 806, which provide a novel approach for        manufactures and producers to promote and display items and for        consumers to window shop and make educated decisions with        respect to items they may be interested in acquiring.    -   G. Consumers 807, representing the end point of the        supply-chain.

In FIG. 8, the solid links terminated by arrows on one end represent thedirectional flow of items through the supply-chain and the broken linksterminated by arrows at both ends represent information flow between thevarious sub-systems and the various physical components of thesupply-chain. In this figure intersecting links should be interpreted asnot connected.

In the diagram of FIG. 8, the retailers 805 represent merchants thatsell items directly to consumers 807. Accordingly, manufacturers andproducers 801, and window shops 806 that sell directly to consumers arealso retailers. For the purpose of this diagram the entities associatedwith these two blocks should be interpreted as playing dual roles. Forexample there is a DELL manufacturer of computers and there is a DELLretailer of computers. For the purposes of FIG. 8, the DELL manufacturerof computers is functionally located in block 801 whereas the DELLretailer of computers is functionally located in block 805. Likewise, awindow shop should be interpreted according to the meaning of block 806,which represents a place where consumers can get information aboutspecific items, and also as a retailer, according to the meaning ofblock 805. For example, a hypothetical “Western Appliance Window Shop”needs to be interpreted in connection with FIG. 8 as being included inboth block 806 for the window shop functions and block 805 for theretail functions.

The diagram of FIG. 8 assumes that there are no stocking distributors inthe supply-chain since one of the purposes of the invention is theelimination on unnecessary inventory in the supply-chain. It isanticipated that during the first few years of operation of thesupply-chain management system 100 there will be some stockingdistributors left. However, they will tend to gradually disappearbecause economic pressures created by the more efficient supply-chainmanagement system.

For simplicity, FIG. 8 does not address service providers and theservices consumers receive from service providers, because servicestypically do not involve the physical delivery of physical objects toconsumers. However, because retailers and window shops can and mayparticipate in offering or providing services to consumers, FIG. 8assumes that services are abstract items that do not require physicaldelivery and service providers are part of manufacturers and producers801.

From a logistic perspective, the operation of supply-chain managementsystem 100 depicted in FIG. 8 can be divided into a procurementfunction, a supply function, a promotion and advertising function, and adata collection function.

The procurement function starts at the consumers 807 and ends at themanufacturers and producers 801 that can supply the items the consumersprocure. In FIG. 8, the elements involved in the procurement functioninclude:

-   -   1. The consumers 807 who procure items.    -   2. The retailers 805 who book purchase orders from consumers for        items the consumers procure.    -   3. The supply-chain management sub-system 106 that coordinates        the propagation of purchase order data in real-time to the        manufacturers and producers 801.    -   4. The predictive ordering sub-system 103 that gives consumers        the opportunity to plan and execute their procurement in advance        of supply in exchange for significant price discounts.    -   5. The consumer preference code sub-system 104 that facilitates        online procurement of non-uniform items by consumers.    -   6. The window shops 806 where preferably consumers can obtain        information about items they are not familiar with but want to        procure.    -   7. The manufacturers and producers 801 who can provide the items        the consumers 807 want to procure.

The supply function starts at the manufacturers and producers 801 andends at the consumers 807. When combined with procurement function itcloses the procurement-supply loop. In FIG. 8, the elements involved inthe supply function include:

-   -   1. The manufacturers and producers 801 who provide the items        ordered by the consumers 807.    -   2. The integrated inventory sharing sub-system 102 that        coordinates the efficient use of regional virtual inventory to        fill orders placed by consumers for immediate delivery.    -   3. The order aggregation management sub-system 101 that gives        consumers the opportunity to specify the date and time, the        location, and the method of receipt of the items provided by the        manufacturers and producers 801.    -   4. The carrier services 802 who physically transport items from        manufacturers and producers 801 to order aggregation facilities        804 and make deliveries to consumers.    -   5. The order aggregation facilities 804 who aggregate orders and        transfer aggregated orders to consumers 807.    -   6. The consumers 807 who receive from the order aggregation        facilities 804 items provided by the manufacturers and producers        801.

The promotion and advertising function relies upon the new promotionmodels described in Section I.D, whereby windows shops and the windowshop management sub-system provide a compelling and effectivealternative to develop consumer awareness of all the items available toconsumers in a global market as opposed to a local market. The promotionand advertising function offers considerable benefits to all theentities participating in the supply-chain management system 100, someof which are:

-   -   1. Manufacturers, producers, and service providers can take        direct advantage of the “window shopping” social need and a        “seeing is believing” strategy to make consumers aware of their        offerings by using the facilities and services provided by        window shops.    -   2. Manufacturers, producers, and service providers can benefit        from the promotional skills of window shop personnel during        consumer visits to window shops.    -   3. Consumers can benefit from a universal catalog of items        (products and services), described later in this section, to get        a global perspective of all the items (products and services)        available in the market place.    -   4. Consumers can benefit from window shops and their staff to        make informed selections and decisions with respect to items        they may interested in acquiring.

The data collection function permeates through the entireprocurement-supply loop and identifies data collection points throughoutthe entire supply-chain management system 100 such that the collecteddata can be used to monitor, control, and manage the operation of theprocurement-supply loop to ensure that the supply-chain managementsystem 100 functions at optimum performance. The data collectionfunction is highly computerized, and offers considerable benefits to allthe entities participating in the supply-chain management system 100,some of which are:

-   -   1. Collects data that support the just-in-time operation of the        supply-chain management system.    -   2. Collects non-predictive purchase order data and predictive        purchase order data that support real-time consumption        monitoring and accurate consumption forecasts.    -   3. Collects accurate regional and global consumption data in        real-time that helps manufacturers and producers manage their        pipeline distribution and bring items jut-in-time to the precise        locations where the items will be consumed.    -   4. Collects personal consumption data to help consumers plan        their future purchases.    -   5. Collects preference code data that enables consumers to shop        online for non-uniform generic items.    -   6. Collects data on consumers' interests, purchase plans, and        comments obtained by window shop personnel during consumer        visits, which can be of important value to manufacturers and        producers.    -   7. Collects data on the physical locations of inventory that        promotes the efficient use and pre-positioning of existing        inventory.

In connection with the operation of the supply-chain management system100 the procurement function involves various steps, next described infurther detail.

A first step associated with the procurement function starts withconsumers 807 placing purchase orders with a plurality of differentretailers 805, as shown by the link between these two blocks. In apreferred embodiment of the invention, the purchase orders booked by theretailers 805 are propagated in real-time to the supply-chain managementsub-system 106 and from the supply-chain management sub-system to thesource manufacturers and producers 801 of the items ordered.

A second step associated with the procurement function addressespredictive purchase orders received by the retailers 805. The predictivepurchase order information can be communicated in real-time to thepredictive ordering sub-system 103 for data compilation and analysis,the results of which can then be propagated in real-time by thepredictive ordering sub-system to manufacturers and producers 801. Thedata generated by the predictive ordering sub-system can also betransmitted through an information link to the supply-chain managementsub-system 106, and further propagated to the integrated inventorysharing sub-system 102 as described later in connection with the supplyfunction.

A third step associated with the procurement function addresses onlineshopping of non-uniform items. In connection with this step, FIG. 8depicts the consumer preference code sub-system 104 with an informationlink to consumers 807. Via this link consumers can access the preferencecode web server 520, depicted in FIG. 5, to register their preferences.In a preferred embodiment, the consumer preference code sub-system 104is integrated into the supply-chain management sub-system 106 via acommunication link between these two sub-systems, as shown in FIG. 8.The consumer preference code sub-system 104 can also have a direct linkto the retailers 805. With this configuration each retailer 805 caneasily access the preference code information of a specific consumer,when needed to book an order from the consumer for a non-uniform itemrequiring a preference code.

A fourth step associated with the procurement function addressesinformation about items. In connection with this step, FIG. 8 depictsthe window shops 806 with an information link to consumers 807 toindicate that consumers can get information about items in which theyhave an interest. Preferably, the window shops 806 have an informationlink to the window shop management sub-system 105, which coordinates theoperation of the window shops and the decentralized exhibition system,described earlier in Section I.D and in Section II.F. The supply-chainmanagement sub-system 106 can have an information link to the windowshop management sub-system 105 to facilitate coordination and exchangeof data. The window shop management sub-system 105 can also have aninformation link to manufacturers and producers 801 through whichmanufacturers and producers can negotiate for the use of window shopfacilities and services.

A fifth and last step associated with the procurement functionterminates the procurement function with a confirmation by themanufacturers and producers 801 that the orders placed by consumers canbe fulfilled by the supply provided by the manufacturers and producers.

In connection with the operation of the supply-chain management system100 the supply function also involves various steps, next described infurther detail.

A first step associated with the supply function takes place at themanufacturers and producers 801 where the items to fill demand byconsumers all over the country start their journey along thesupply-chain. Preferably, for each of the items provided by each of themanufacturers and producers a three dimensional planning map of quantityto meet demand versus geographic location and date/time is generatedfrom accurate consumption forecasts provided by the supply-chainmanagement sub-system 106. Based on this map, manufacturers andproducers can plan bulk shipments to regional distribution centers 803around the country just-in-time to fill orders to be aggregated by theorder aggregation facilities 804 serviced by each of the regionaldistribution centers 803 and other purchases made by consumers fromlocal retailers.

A second step associated with the supply function relates to theintegrated inventory sharing sub-system 102, which addresses theresidual discrepancies between forecasted demand and actual demand. Thesupply-chain management system 100 is configured to accurately forecastdemand versus calendar time and geographic location. Based on theforecasted demand, the supply-chain management system attempts to moveitems along the supply-chain pipeline to closely match the forecasteddemand but still needs to maintain a minimum amount of regionalinventory to accommodate minor fluctuations in local consumption withinthe margin of error of consumption forecasts. Based upon the margin oferror, the integrated inventory sharing sub-system 102 can establishregional levels of virtual inventory for the operation of the integratedinventory sharing sub-system 102 on a regional basis, as described inSection II.E. From this perspective, the integrated inventory sharingsub-system 102 operates as a local virtual inventory provider to addressthe situations where a consumer has an immediate unanticipated need fora given item. To coordinate the use of this small local virtualinventory buffer, the supply-chain management sub-system 106 can use acommunication link to the integrated inventory sharing sub-system 102.

A third step associated with the supply function relates to the orderaggregation management sub-system 101, which addresses the efficient andcost effective transfer of items to consumers. The order aggregationmanagement sub-system is the key coordinating element for the supplyfunction. In connection with the placement of purchase orders,preferably consumers provide order aggregation instructions eitherconcurrently with or subsequently to the placement of each purchaseorder. For many consumers, order placement will tend to occur in cycleswhereby the transfers of aggregated orders to each consumer may occur atregular intervals. For the purposes of illustration consider the case ofa consumer that develops a pattern of scheduling receipt of aggregatedorders on Fridays for the orders placed during a cycle extending fromSaturday through Friday. After the end of a particular cycle, assume theconsumer makes the first purchase on Sunday and leaves the date and timefor receiving the order open. On Wednesday, the consumer makesadditional purchases and has sufficient visibility to schedule a pick upat a nearby order aggregation facility at 4:40 PM on Friday, on the wayhome from a dental appointment. The consumer decides to have the itemsordered on Sunday and Wednesday aggregated for the Friday pick up. OnThursday the consumer makes various additional purchases from differentretailers and the order aggregation management sub-system suggests tothe consumer that the new orders be aggregated with the previouslyscheduled orders. The consumer agrees and on Friday at 4:40 PM all theitems ordered by the consumer Sunday through Thursday are ready for pickup at the order aggregation facility 804 selected by the consumer.

Preferably, the order aggregation management sub-system 101 has aninformation link to the supply-chain management sub-system 106 toreceive in real-time purchase order information as orders are booked. Inmost cases information related to order aggregation instructions, dateand time for the receipt of aggregated orders, and pick up or deliveryoptions is collected when an order is booked. In other cases theconsumers 807 provide this information to the order aggregationmanagement sub-system 101 through a direct link after the order isbooked, as illustrated in the example above. After all the requiredpurchase order data and aggregation and delivery data is collected, theorder aggregation management sub-system 101 communicates through a linkto the manufacturers and producers 801 shipping instructions for theitems sold. Through a link to the carrier services 802 the orderaggregation management sub-system 101 communicates transportationschedules to the carrier services for the transportation of the items tobe shipped just-in-time from the source manufacturers and producers 801to the order aggregation facilities 804 designated to receive theshipments. Through a link to the order aggregation facilities 804, theorder aggregation management sub-system 101 provides to the orderaggregation facilities order aggregation instructions. Based on theseinstructions, each order aggregation facility physical aggregates theitems received in batches of physically aggregated orders and transfersthe physically aggregated batches to the consumers scheduled to receiveaggregated orders.

A fourth step associated with the supply function relates to the carrierservices 802 that provide just-in-time transportation services for theitems purchased by consumers. These items are transported frommanufacturers and producers 801 to the local order aggregationfacilities 804 in the various regions of the country in compliance withthe schedules for aggregation and delivery of aggregated orders toconsumers. This step is preferably performed by the carrier services 802in conjunction with the distribution centers 803 and is described infurther detail below with reference to FIG. 9. In a preferredembodiment, the distribution centers 803 are managed by the carrierservices 802 and may be operated independently or integrated as part ofthe carrier services in accordance with models presently used bycarriers such as UPS or FEDEX. Preferably, the order aggregationmanagement sub-system 101 uses a communication link to the carrierservices 802 to provide the carrier services with transportationinstructions for moving the items purchased by consumers along thesupply-chain. To facilitate the coordination of just-in-timetransportation, the carrier services 802 can use communication links tothe manufacturers and producers 801, distribution centers 803, and orderaggregation facilities 804.

A fifth and last step associated with the supply function occurs at eachof the order aggregation facilities 804, where each aggregated order istransferred to the respective consumer 807. This step is executed byeither having the consumer pick up the aggregated order at the selectedorder aggregation facility 804 or by having the carrier services 802pick up the aggregated order at the order aggregation facility 804 anddeliver it to an address designated by the consumer 807.

At the regional level the carrier services for transportation fromregional distribution centers to order aggregation facilities and fromorder aggregation facilities to consumer residences could beadvantageously integrated with commercial carriers that make localdeliveries such as UPS and FEDEX. Further, the commercial carriers couldprovide the local carrier services for the supply-chain managementsystem. Parcel deliveries to consumers normally made by commercialcarriers could be delivered not to consumer residences, but instead toorder aggregation facilities to be aggregated with consumer ordersalready scheduled for aggregation. In addition parcels consumers need toship could be processed through order aggregation facilities. Forexample a consumer picking up an aggregated order at an orderaggregation facility could also drop off at the order aggregationfacility a parcel to be shipped. Likewise, a carrier service deliveringan aggregated order to a consumer residence, could also pick up a parcelthe consumer wishes to ship. Such integration could provide a favorablesynergy by significantly reducing the total miles driven by commercialcarriers in connection with local deliveries and miles driven byconsumers in connection with shopping and shipping parcels. Suchreductions in miles driven can translate in significant reductions incosts, pollution, time wasted, and use of energy.

With respect to the operation of the carrier services 802 in conjunctionwith the distribution centers 803, FIG. 9 provides a diagrammaticalrepresentation that illustrates further details about the operation ofthe carrier services 802 and distribution centers 803 to perform thejust-in-time transportation of items from each manufacturer or producer801 to the consumers 807. The distribution centers 803 of FIG. 8 areseparated in FIG. 9 into intermediate distribution centers 901 andregional distribution centers 902. This configuration can be used toprovide flexibility, optimize the operation of the carrier services, andminimize transportation costs. Also the consumers 807 of FIG. 8 areseparated in FIG. 9 into consumers that elect to pick up aggregatedorders 903 and consumers that elect to have aggregated orders delivered904.

Typically items will be transported from the manufacturers and producersto intermediate distribution centers, from intermediate distributioncenters to regional distribution centers and finally from regionaldistribution centers to specified order aggregation facilities servicedby the regional distribution centers.

The logistics and configuration of intermediate and regionaldistribution centers and the operation of carrier services to minimizetransportation costs in large volume operations are well understood bythose skilled in the art and will not be further described.

As shown in FIG. 9, the carrier services typically follow a primary setof long distance routes 905 to carry truck loads of items from themanufacturers and producers 801 to intermediate distribution centers901. For manufacturers or producers that ship small loads insufficientto fill a truck, concentration centers can be used, not shown in FIG. 9,to combine multiple shipments of small loads into full truck loads toimprove the utilization of transportation equipment.

From the intermediate distribution centers 901, the carrier servicestypically follow a secondary set of routes 906 to carry truck loads ofitems to regional distribution centers 902 that service regionalpopulation centers.

From the regional distribution centers 902, regional carrier servicesfollow regional routes 907 to transport the items purchased by consumersto a variety of order aggregation facilities dispersed within thepopulation centers. In a preferred configuration, the regionaldistribution centers are located on the outskirts of the populationcenters, a strategy that offers two advantages. First, the use of spacecosts much less on the outskirts of population centers and second thetruck loading factor for the regional transportation can significantlyincrease. To illustrate consider the following example:

Assume that regional distribution center “A” expedites items sent to theregion by manufacturers “X” and “Y”. A local transportation truckdeparts from distribution center “A” with a full load of these items anddrops various loads at a sequence of order aggregation facilities (OAF)804 along a given route 907 to meet the aggregation instructions atthose order aggregation facilities. Along the way it picks up aggregatedorders from order aggregation facilities 804 and delivers them to theresidences of local consumers 904 close to given route. While deliveringaggregated orders it can also pick up consumer returns and executetransfers from one order aggregation facility to another also along thegiven route. Eventually it reaches regional distribution center “B”,that expedites items sent to the region by manufacturers “Z” and “W”, atthe opposite end of the population center. At distribution center “B”,the truck picks up a full load of these different items and the processbetween “A” and “B” is then repeated between “B” and “C”, etc.

This model allows the trucks to travel between different types ofdistribution centers 902 to make a coordinated distribution of items toorder aggregation facilities 804 in compliance with preset schedules todeliver the items to consumers. Along the routes the trucks also makeresidential deliveries and transfer orders between order aggregationfacilities to accommodate last minute changes in pick up instructionsrequested by consumers. Based upon this model, the local carrierservices can operate their trucks at an average loading factor well inexcess of 50%. If the local parcel deliveries are integrated within thesupply-chain management system as discussed previously, then the averageloading factor can be significantly higher.

In contrast, local distribution systems operating in accordance withtraditional models typically operate below 50% loading capacity asillustrated in the following example. Assume ideal circumstances wherebya UPS truck leaves a UPS depot with a full load of parcels to makedeliveries to a plurality of places along a given route. Assume furtherthe ideal circumstances whereby the truck follows a circular route withevenly spaced deliveries. Under these ideal assumptions the truck startsfull and arrives empty indicating that the average load during the routeequates to 50%. Under typical non-ideal circumstances the outcome ismuch worse. First the route is not circular but instead goes to an enddestination for the last delivery and then the truck turns around andmakes a trip back completely empty and second the truck does not departwith a full load because of uncontrollable fluctuations in daily volume.The result is a typical loading factor well below 50%.

This introductory section has provided a panoramic overview of theoperation of the supply-chain management system 100 to facilitate thedetailed description of the operation of the six sub-system componentsintegrated into the supply-chain management system 100, which wereintroduced earlier in Section II. Sections III.A through III.F, below,describe the operation of each of those sub-system components.

A. Operation of the Order Aggregation Management Sub-System

The order aggregation management sub-system 101 was described in SectionII.A as a key sub-system component of the supply-chain management system100. This section describes, with reference to FIGS. 10A-C an orderaggregation method 1000 preferably performed by the order aggregationmanagement sub-system.

At step 1001, identifying a plurality of consumers using thesupply-chain management system 100 for shopping. Preferably consumersregister as users of the supply-chain management system by visiting asecure registration web site to setup a user profile. For users toderive maximum benefits from the supply-chain management system the userprofile is preferably configured to receive user information thatincludes the following:

-   -   1. Personal login identification (required).    -   2. Password (required).    -   3. User name (optional). Having the user's name facilitates        communication with the user.    -   4. Default address (optional). Registering a default address        saves the user the time to enter a delivery address for home        deliveries.    -   5. Default phone number (optional). Registering a default phone        number allows the supply-chain management system to provide the        user any applicable notifications and respond to user's        inquiries.    -   6. Default email address (optional). Registering a default email        address facilitates communications with the user.    -   7. Default order aggregation facility for user to pick up        aggregated orders (optional). Registering a default order        aggregation facility saves the user the time to enter an order        aggregation facility if the user has a preferred order        aggregation facility.    -   8. Default payment method and information (optional).        Registering a default method of payment saves the user the time        for entering payment information for each purchase order.

At step 1002, identifying a plurality of merchants participating in thesupply-chain management system 100. To participate in the supply-chainmanagement system each merchant needs to provide the merchant data 211described in Section II.A.

At step 1003, identifying a plurality of order aggregation facilitiesparticipating in the supply-chain management system.

At step 1004, identifying for each of the identified consumers itemspurchased by the consumer from the identified merchants, wherein theitems are designated for aggregation in a batch. As described in SectionII.A, when a consumer places a purchase order with a merchant, the itemson the purchase order are identified. Further, if the consumer wishesthat at least some of the items in one or more purchase orders placed bythe consumer be physically aggregated in a batch for delivery to theconsumer, such items are designated for physical aggregation in a batch.The default can designate all items purchased by the consumer forphysical aggregation unless the consumer specifies another alternative.For example, a consumer may designate that large appliances are not tobe aggregated with other items.

At step 1005, identifying for each of the identified consumers an orderaggregation facility where the items in the batch will be physicallyaggregated.

At step 1006, identifying for each of the identified consumers orderaggregation instructions for the items in the batch to be physicallyaggregated.

At step 1007, identifying for each of the identified consumers a dateand time for transferring the batch of physically aggregated items tothe consumer. Preferably, the order aggregation facility receivesshipments of items to be physically aggregated within one or two hoursof the identified time for transfer. For example, consecutive timewindows of one hour can be established and the items to be transferredto consumers during a given time window can be scheduled to arrive atthe order aggregation facility during the second time window before thegiven time window i.e. at least one hour before the hour during whichthe items are transferred to the consumer.

At step 1008, identifying for each of the identified order aggregationfacilities aggregation schedules compliant with order aggregationinstructions for the batches of items to be physically aggregated by theorder aggregation facility.

At step 1009, instructing each of the identified merchants to group theitems purchased by consumers in separate groups, whereby each groupconsists of items to be physically aggregated at a same identified orderaggregation facility at proximate times.

At step 1010, instructing each of the identified merchants to ship eachof the separate groups of items to the same identified order aggregationfacility just-in-time in compliance with aggregation schedules for theitems to be aggregated at the same order aggregation facility.

Steps 1009 and 1010 are intended to reduce transportation costs asillustrated in the following example. A large producer of dairy itemsservices a number of regional areas in the eastern part of the US from acentral facility. Every 4 hours, the producer of dairy items computesfor each item a shipping matrix of quantities required to fill consumerpurchase orders versus order aggregation facility and time window,wherein the time window is expressed in one hour increments. Based onthe shipping matrix, the producer of dairy items schedules bulkshipments of each item to regional distribution centers that service thevarious regional areas to cover deliveries for a 4 hour period. From theregional distribution centers, distribution routes and schedules can becomputed each hour to deliver the required quantity of each item to eachorder aggregation facility in compliance with the pre-defined orderaggregation schedules for each consumer. For simplicity, this exampleaddresses the simple case of one producer. However, in the general caseof multiple manufacturers and producers operating from the same city orgeographic location, bulk shipments from different manufacturers andproducers may be combined to improve transportation efficiency. Inaddition, intermediate distribution centers may be required to optimizetransportation logistics, as discussed earlier in this section. Thegeneral problem of optimizing transportation of items from a pluralityof sources to a plurality of destinations is well understood by thoseskilled in the art and in particular by commercial carriers and need notbe further illustrated.

At step 1011, providing each of the identified order aggregationfacilities advance notice of groups of items to be received. Preferably,the order aggregation management sub-system 101 provides each orderaggregation facility a detailed schedule of items to be expected and,for verification purposes, the carrier services can also inform eachorder aggregation facility of the anticipated deliveries. Should therebe any discrepancies, the order aggregation management sub-system 101can be timely informed and take the appropriate corrective action.

At step 1012, instructing each of the identified order aggregationfacilities to receive the groups of items shipped by merchants.

At step 1013, providing to each of the identified order aggregationfacilities the identified order aggregation instructions for eachconsumer scheduled to receive a physically aggregated batch from theorder aggregation facility.

At step 1014, instructing each of the identified order aggregationfacilities to aggregate the items received from the merchants inaccordance with the provided aggregation instructions for each consumer.

In connection with steps 1010-1012, the order aggregation facilitypreferably receives the items to fill consumer aggregated orders in bulkand executes the aggregation by performing the pick and pack for eachconsumer based upon the aggregated list of all the items purchased bythe consumer from multiple merchants.

At step 1015, instructing each of the identified order aggregationfacilities to transfer to each of the consumers scheduled to receive abatch of physically aggregated items designated for pick up, the batchof physically aggregated items at the identified date and time.

At step 1016, instructing each of the identified order aggregationfacilities to deliver to each of the consumers scheduled to receive abatch of physically aggregated items designated for delivery, the batchof physically aggregated items at the identified date and time to anaddress designated by the consumer.

Steps 1015 and 1016 relate to the two choices offered to the consumer toreceive a physically aggregated order. According to the first choice,the consumer can pick up the aggregated order at an order aggregationfacility of the consumer's choice at a date and time selected by theconsumer. According to the second choice, the consumer can have thephysically aggregated order delivered to an address designated by theconsumer at a date and time selected by the consumer. In the second casethe order aggregation management sub-system 101 preferably determinesthe order aggregation facility from where the delivery will be made andthe carrier services 802 will execute the delivery as part of theirroutine operations.

The order aggregation method just described ensures just-in-timetransportation of items from the point of origin to the consumer's doorstep, eliminates the cost of inventorying items at retailers facilities,fully expands the item selections available to consumers to a level thatcould not be met by shelf space in retail stores, and ensures thefastest availability to consumers.

B. Operation of the Integrated Inventory Sharing Sub-System

The integrated inventory sharing sub-system 102 was described in SectionII.B as a key sub-system component of the supply-chain management system100. This section describes, with reference to FIG. 11 an integratedinventory sharing method 1100 preferably performed by the integratedinventory sharing sub-system.

At step 1101, identifying a plurality of merchants participating in theintegrated inventory sharing sub-system. Promotion and advertising canbe used to invite merchants to participate in the integrated inventorysharing sub-system and merchants can register to participate via thevirtual inventory web server 320 described in Section II.B.

At step 1102, identifying the merchant sharing data of each merchant.

At step 1103, storing the merchant sharing data of each merchant in theinventory sharing database system 310. A forms interface can be providedto help each merchant initially identify its merchant data. Once themerchant data is identified and verified, the data entry and retrievalprogram 321 can be used to upload the merchant data in the inventorysharing data database system 310.

At step 1104, computing the virtual inventory data 312 based at least onthe merchant sharing data of each merchant.

At step 1105 storing the computed virtual inventory data in theinventory sharing database system 310. Preferably, when the integratedinventory sharing sub-system 102 is first installed, the virtualinventory data for the initial participating merchants is computed andstored. Thereafter, the virtual inventory can be maintained throughreal-time updates.

At step 1106, updating in real-time the virtual inventory data in theinventory sharing database system 310 upon a change of the merchantsharing data of a merchant. Examples of a change of the merchant sharingdata of a merchant include:

-   -   1. Receipt of new inventory.    -   2. Sale of an item in inventory to a consumer or another        merchant.    -   3. Return of an item in inventory to the original manufacturer        or producer.    -   4. Accidental loss of an item.    -   5. Placing an item on temporary reservation in connection with a        consumer request for quote.    -   6. A change in bid and ask prices and quantities posted by the        merchant.    -   7. A new merchant that joins the integrated inventory sharing        sub-system.

At step 1107, responding in real-time to queries related to virtualinventory data and merchant sharing data submitted to the inventorysharing data database system 310.

At step 1108, generating a bid and ask market to facilitate transactionsamong the identified merchants by matching in real-time for eachmerchant of the identified merchants bid prices and quantities providedby the merchant for an item to ask prices and quantities provided byeach other merchant of the identified merchants for the item.Preferably, the bid and ask market is generated by the market makingprogram 325 described in Section II.B.

At step 1109, executing and processing inventory transactions performedby and between the merchants. Preferably, inventory transactions amongmerchants are executed by the transaction processing program 324described in Section II.B.

To illustrate consider the following case: merchant “A” is about to runout of “Samuel Adams Cream Stout” beer and through the market makingprogram identifies several merchants holding surplus inventory wherebythe lowest ask price is $21.75. Merchant “A” places a bid for 6 cases at$21.75 per case on the market making program 325 with a preference toobtain the beer from the closest merchant within a 10 mile radius. Themarket making program 325 automatically identifies among the merchantsposting a $21.75 ask price a merchant “B”, located 5 miles from merchant“A”, and executes and processes the transaction. In the inventorysharing data database system 310 the 6 cases of beer are automaticallytransferred from the inventory of merchant “B” to the inventory ofmerchant “A”. The transaction processing program 234 automaticallycredits $130.50 ($21.75×6) to the account of merchant “B” and debits theaccount of merchant “A” $130.50 plus $0.97 for transport charges. Thetransaction processing program 234 also notifies the carrier services topick up the 6 cases of beer from merchant “B” and deliver them tomerchant “A”. Because the carrier services have extensive operations inthe area, the transport of the beer should be completed within one hourat minimum cost.

A better alternative is to let the beer remain at merchant “B”. Merchant“A” continues to sell the newly acquired “Samuel Adams Cream Stout”,which eventually needs to be transported to one or more orderaggregation facilities to fulfill purchase orders from consumers. Theorder aggregation management sub-system 101 has real-time informationabout the physical location of all existing inventory of “Samuel AdamsCream Stout” in the region and can utilize the inventory as needed tominimize transportation costs. In this regard, each merchant holdingvirtual inventory operates as a mini distribution center from which theorder aggregation management sub-system 101 can pull inventory to supplyorder aggregation facilities.

A general operating rule for the most efficient operation of thesupply-chain management system is to supply the needs of each orderaggregation facility from the pipeline inventory geographically locatedclosest to the order aggregation facility provided it does not violateany committed schedules.

C. Operation of the Predictive Ordering Consumption ForecastingSub-System

The predictive ordering sub-system 103 was described in Section II.C asa key sub-system component of the supply-chain management system 100.This section describes, with reference to FIGS. 12-17 methods for theoperation of the predictive ordering sub-system for each item subject toa predictive price discount.

FIG. 12 describes a preferred predictive ordering method 1200 for usingthe predictive ordering sub-system 103.

At step 1201, identifying a plurality of consumers using thesupply-chain management system for shopping.

At step 1202, identifying an item subject to a predictive pricediscount.

At step 1203, identifying a plurality of merchants providing the itemsubject to a predictive price discount.

At step 1204, identifying a predictive discount schedule of predictiveprice discount versus predictive order delay (POD) applicable to theitem. Preferably, the predictive discount schedule for each item isgenerated by the manufacturer, producer, or service provider thatprovides the item, based upon the estimated primary cost savingsrealized by the manufacturer, producer, or service provider andsecondary costs savings realized by other participants in thesupply-chain.

At step 1205, informing each of the identified merchants of thepredictive discount schedule applicable to the item. Although merchantsare free to set their retail prices independently, the predictivediscount schedules are preferably applied globally on a percentage basisby all participating merchants to support optimum performance of thepredictive ordering sub-system 103. For example, if merchant “A” retailsitem “I” for $64.99 and merchant “B” retails the same item “I” for$69.99 a predictive price discount of 20% for a predictive order delay(POD) of 15 days would be equally applied to the retail prices $64.99and $69.99 independently of the merchant.

At step 1206, informing the identified consumers of the predictivediscount schedule applicable to the item. For consumers to takeadvantage of predictive price discounts it is important that consumersbe timely informed of such discounts. This is what happens within thetraditional distribution systems when promotional fliers are used toinform consumers of promotional discounts. The traditional promotionalfliers use a counter productive process involving the costs of printingand distributing the flyers, the time wasted by consumers to read theflyers to find very few items of interest, the time and mileage costsexpended by consumers to purchase the few items during the promotionalperiod, and subsequently the cost of disposing of the incrementalgarbage generated by the flyers. With the supply-chain management system100 the traditional counter productive promotional flyers can becompletely eliminated by the use of the shopping list generationprograms and automatic shopping programs introduced in Section I.A inconnection with shopping models. The shopping list generation programand the automatic shopping programs can be configured to receive alertsof favorable predictive price discounts. The shopping list generationprogram can suggest to the consumer stocking up on a specific item andautomatically estimate the quantity to be ordered to minimize the annualconsumer expense based upon the capability of the shopping program toautomatically shop for the lowest available price. These programs canoffer consumers significant savings of time and costs.

At step 1207, generating consumption forecasts for the item, wherein theconsumption forecasts for the item are based at least upon predictivepurchase orders booked for the item by the identified merchants,analyzed real consumption data for the item, and historical correlationsbetween predictive and non-predictive purchase orders booked for theitem.

At step 1208, informing in real-time each of the identified merchants ofconsumption forecasts generated for the item. Typically, the merchantsproviding the item start with the source manufacturer, producer, orservice provider of the item and end with the retailers that bookpurchase orders from consumers for the item. There may also beintermediate merchants such as wholesalers and distributors, althoughthese intermediate merchants may gradually be replaced by a modelwhereby manufacturers and producers own and control the pipelineinventory.

To derive maximum benefits from the predictive ordering sub-system,manufacturers, producers and service providers need to obtain inreal-time the ordering information for the predictive purchase ordersbooked by merchants participating in the supply-chain management system100. Preferably, the large majority of participating merchants will beequipped with computer systems configured to communicate with thesupply-chain management sub-system 106 to provide order booking data inreal-time. Based on this configuration, the supply-chain managementsub-system can automatically collect predictive ordering data from theparticipating merchants equipped with these computer systems. Thecollected data can be periodically compiled and summary reports can begenerated.

Regular consumption data not associated with predictive purchase orderscan also be compiled and summarized in real-time. The predictive and thenon-predictive purchase orders can then be combined to provide sourcemanufacturers, producers and service providers real-time statisticaldata on real consumption and reliable consumption forecasts. Initially,the periodicity may be in the order of hours but over time it may bereduced to less than one minute, whereby a manufacturer may be able tosee on a computer display a steaming plot showing the rate of sales fora given item, including an extension into the future (preview) basedupon predictive purchase orders booked.

The operation of the predictive ordering sub-system 103 depends in parton the capability to estimate cost savings realized by the supply-chainas a result of accurate forecasts of future consumption. FIG. 13illustrates a hypothetical three dimensional plot 1301 of estimated %cost savings versus predictive order delay and predictive order volumefor a hypothetical item.

In this diagram, the horizontal plane consists of the predictive orderdelay (POD) axis 1302 and the predictive order volume axis 1303. Thevertical axis represents the % cost savings 1304. For a very smallpredictive order volume, the % cost savings versus the predictive orderdelay (POD) is illustrated by the “S” shaped the curve 1305, whichshould be interpreted as a curve drawn on the plane defined by thepredictive order delay (POD) axis 1302 and the % cost savings axis 1304.

As indicated by the “S” shaped curve 1305, for a very small POD, the %cost savings should be insignificant. As the POD increases, the % costsavings should first increase to a maximum slope and then progressivelylevel off at a value representing the maximum achievable % cost savingsfor large POD values. In most cases, the % cost savings should have astrong correlation to a manufacturing or production cycle time. Forexample, a future demand visibility extending over two manufacturingcycles allows a certain manufacturer to optimize productivity bymanufacturing quantities that closely match demand.

In the plane 1306 where the POD is zero, defined by the volume axis 1303and the % cost savings axis 1304, the curve 1307 represents the typicalquantity volume discounts offered by manufactures and producers forvolume orders. This curve indicates that manufactures and producers canafford to give discounts for volume orders because increased volumeresults in cost savings. FIG. 13 illustrates a sequence of planesparallel to plane 1306, including plane 1308 and plane 1310. Each of theplanes in this sequence corresponds to an increasing value of the PODalong the predictive order delay (POD) axis 1302 and displays a curvereflecting the increase in the % cost savings with increasing volume.For example, plane 1308 shows curve 1309 with the small volume % costsavings starting at 8.75% and climbing to 42.5% for large volume andplane 1310 shows curve 1311 with the small volume % cost savingsstarting at 30% and climbing to 52.5% for large volume.

Although the major portion of the total supply-chain cost savings isexperienced by the manufacturers and producers, other segments of thesupply-chain can also experience cost savings. Carrier services canoperate more efficiently by receiving in advance reliable information onthe transportation services they are asked to provide because they canbetter plan the use of resources to maximize productivity. Distributioncenters at all levels can operate with minimum service space andpersonnel because they can plan in advance. Retailers can operate withminimum inventory, space, and personnel because quantities receivedclosely match quantities delivered to consumers on a daily basis. Thecost savings experienced by the other segments of the supply-chain maybe difficult to theoretically predict due to the diversity of potentialfactors affecting cost savings. However, once the supply-chainmanagement system is deployed it should be relatively easy to establishthese cost savings empirically.

After the supply-chain cost savings are established, the predictiveprice discounts offered to consumers as an incentive for the consumersto use the predictive ordering sub-system need to be identified andoptimized to produce the desired results. This aspect involves acomponent associated with consumer behavior and a component associatedwith consumer response to the benefits provided by the predictiveordering sub-system.

FIG. 14 illustrates a hypothetical three dimensional correlation 1401 ofpredictive order volume versus predictive order delay (POD) andpredictive price discount. The horizontal plane is defined by thepredictive order delay axis 1402 and the predictive price discount axis1403. The vertical axis represents the predictive order volume 1404. Inthe horizontal plane the “S” curve 1405 represents a specific scheduleof predictive price discounts versus predictive order delays. For thisspecific schedule, the predictive order volume is represented by a setof the vertical bars. Bar 1406 is an example of one of these bars thatoriginates at a point 1407 along the “S” curve 1405 drawn on the twodimensional space of the variables predictive price discount andpredictive order delay. The “S” curve 1405 can be adjusted withinreasonable boundaries reflecting external limitations. For example, thepredictive price discount versus predictive order delay (POD) for verysmall volumes (near curve 1405) should not exceed the % cost savingsversus predictive order delay (POD) for very small volumes indicated bycurve 1305 in FIG. 13. Another limitation reveals no need to considervalues for the POD in excess of a several times the manufacturing orproduction cycle since the % costs savings tend to reach a plateau afterthis range. When the “S” curve 1405 is adjusted, the tops of the bars1406 generate a surface defining an implicit function of the variablespredictive order volume, predictive order delay (POD), and predictiveprice discount. This surface provides the foundation for empiricallyoptimizing price discounts as described next with reference to FIG. 15.

FIG. 15 illustrates a predictive price discount optimization method 1500preferably performed by the predictive ordering sub-system based uponthe concepts outlined in connection with FIGS. 13 and 14.

At step 1501, identifying an item subject to a predictive pricediscount.

At step 1502, associating with the item variables expressing predictiveorder volume, predictive order delay (POD), and predictive pricediscount.

At step 1503, defining a first function associated with the itemcorrelating the variables predictive order volume, predictive orderdelay (POD), and predictive price discount. This first function is theimplicit function of the variables predictive order volume, predictiveorder delay (POD), and predictive price discount described above withreference to FIG. 14.

At step 1504, identifying a parameter associated with the item that isaffected by the first function correlating the variables predictiveorder volume, predictive order delay (POD), and predictive pricediscount. Manufacturers and producers can make parameter selectionsbased upon considerations that reflect business strategies. For example,a manufacturer wishes to maximize sales volume to phase out an oldversion of an item from a production line to facilitate the introductionof a new version. In a different example, a manufacturer with a steadyproduction line operation wishes to optimize profitability.

At step 1505, defining a second function that correlates the identifiedparameter to the first function correlating the variables predictiveorder volume, predictive order delay (POD), and predictive pricediscount.

At step 1506, based at least on the second function, identifying apredictive discount schedule of predictive price discount versuspredictive order delay (POD) that optimizes the parameter associatedwith the item.

At step 1507, applying the identified predictive discount schedule tothe item. Preferably, a price discount schedule remains in effect untila new price discount schedule is identified and made effective.Typically, the source provider of the item determines the time when anew predictive discount schedule becomes effective based mostly uponbusiness considerations.

Preferably, the supply-chain management system adopts a strategy wherebythe source provider of the item is responsible for posting predictivediscount schedules on the predictive ordering web server to maintain thepredictive ordering database system current. Based on this strategy, anew predictive discount schedule can be implemented concurrently by allthe identified merchants. Automatic shopping programs used by consumerscan be notified in real-time of new predictive price discounts postedfor an item and determine if the consumer should take advantage of theprice discounts.

Among the diversity of criteria that can be selected as a basis tooptimize a predictive discount schedule, one criterion is associatedwith consumption stability and could have a significant impact in stableeconomic growth. This criterion deserves further disclosure.

Free market economies are inherently unstable economic models subject tocyclic fluctuations related to propagation delays in the market forcesthat are supposed to provide stabilizing effects. This inherentinstability could be attenuated by the use of a fast reactionauto-regulation mechanism. A potential auto-regulation mechanism is thepredictive ordering sub-system 103, which can provide the basis for aconsumption cruise control system and method with the potential ofsignificantly attenuating or even eliminating undesirable fluctuationsin consumption.

FIG. 16 provides a block diagram of a preferred embodiment of analgorithmic closed loop control system 1600 for consumption cruisecontrol and FIGS. 17A-B illustrate a preferred consumption cruisecontrol process 1700 for using the algorithmic closed loop controlsystem 1600 to stabilize the consumption of an item. FIGS. 16 and 17refer to several parameters and variables which include the following:

-   -   1. A “time unit” defined as the unit selected to express a time        variable. For the purpose of this illustration, a time unit of        one week is selected.    -   2. A “look back interval” defined as a time interval expressed        in time units extending in time back from the end of a current        time unit. For example, the look back interval can be set at 20        weeks back from the end of the current week.    -   3. A “look forward interval” defined as a time interval        expressed in time units, extending in time forward from the end        of a current time unit. For example, the look forward interval        can be set at 6 weeks forward from the end of the current week.    -   4. A “time window” defined as a time interval obtained by        appending the look forward interval to the look back interval.        For example, if the look back interval is 20 weeks and the look        forward interval is 6 weeks, the time window is 26 weeks.    -   5. A “control interval” defined as a time interval between two        consecutive cycles of the algorithmic closed loop control        algorithm. For the purpose of this illustration, a control        interval of one week, corresponding to one time unit, is        selected.    -   6. A “current control interval” defined as the control interval        associated with a cycle of the algorithmic closed loop control        algorithm being executed.    -   7. A “baseline consumption rate” of an item defined as a        variable representing a disturbance free ideal consumption of        the item per time unit.    -   8. A “real consumption rate” of an item defined as the total        quantity of the item acquired by consumers per time unit. The        real consumption rate may experience fluctuations from one time        unit to the next (week to week).    -   9. A “look forward consumption rate” of the item defined as a        variable representing a projected consumption rate of the item        versus time over the look forward interval. The look forward        consumption includes two components. The first is a predictive        consumption rate computed from booked predictive purchase orders        scheduled for delivery during the look forward interval. The        second is a non-predictive consumption rate computed from        non-predictive purchase orders estimated to occur during the        look forward interval.    -   10. A “control function” defined as a function that expresses        the appropriate level of control action necessary to maintain        the real consumption of the item close to the baseline        consumption.

FIG. 16 starts with a baseline consumption rate estimator 1601 thatestimates what the consumption rate should be over the time window underideal conditions free from consumption disturbances. The baselineconsumption rate estimator estimates an ideal consumption rate from theperspective of the manufacturer or producer of the item underconsideration. In one embodiment, the estimate is based upon historicalconsumption rates, consumption rates observed during the look backinterval, observed growth in consumption rate, applicable seasonalfactors, manufacturing and production resources, use of naturalresources, long-term price stability, inflation, general economicstability and growth, preservation of the environment and any otherfactors identified by the manufacturer or producer that may impact thebaseline consumption rate. The estimated baseline consumption rate canbe stored in a baseline consumption rate database 1602 that storesbaseline consumption rate versus time and can be kept current with themost recent baseline consumption rate estimate.

During the look forward interval the two components of the consumptionrate are:

-   -   a) The “predictive consumption rate” for each time unit of the        look forward interval 1603, which is computed from booked        predictive purchase orders. To obtain accurate projections,        adjustments for cancellations can be made to the booked        predictive purchase orders based on historical records of        cancellations and then an adjusted predictive consumption rate        can be computed for each time unit.    -   b) The “non-predictive consumption rate” for each time unit of        the look forward interval 1604, which is an estimated        consumption rate. It is anticipated that there will be a strong        correlation between predictive purchase orders and        non-predictive purchase orders since the correlation involves a        personal preference which tends to be stable. Based on this        correlation and historical data of non-predictive purchase        orders, the volume of non-predictive purchase orders can be        estimated with good accuracy during the look forward interval.

The real consumption rate database 1605, stores in real-time the realconsumption rate that takes place over time. For each item, the realconsumption rate can be expressed in real consumption per time unit.

The algorithmic closed loop controller 1606 is the active component ofthe algorithmic closed loop control system 1600. The algorithmic closedloop controller receives as inputs:

-   -   1) The baseline consumption rates, from the baseline consumption        rate database 1602. Although the baseline consumption rate        database preferably keeps records of baseline consumption        estimates made over time, the most relevant data is related to        the baseline consumption estimates for the current control        interval.    -   2) The real consumption rates from the real consumption rate        database 1605. Although the real consumption rate database 1605        keeps records of the real consumption rate from the first time        unit to the current time unit, the most relevant data is related        to the real consumption rates for the current control interval.    -   3) The predictive consumption rate for each time unit of the        look forward interval 1603, preferably adjusted for        cancellations.    -   4) The non-predictive consumption rate for each time unit of the        look forward interval 1604, estimated from historical        non-predictive consumption rate data and correlations with        predictive consumption rate data.

Based upon these four inputs, the algorithmic closed loop controller1606 preferably generates a control function to be applied to the realconsumption. Most closed loop control system designs can only rely onthe deviation between the current value and the desired value of aprocess parameter because they do not benefit from a look forwardmonitoring capability. As a result, these systems are always subject toa theoretical residual control error. In contrast, the algorithmicclosed loop controller 1606 has the capability of looking into thefuture and take corrective action before potential deviations from thedesired baseline consumption occur.

In a preferred embodiment, the control function is the predictive pricediscount versus predictive order delay (POD) offered to consumers,described earlier in this section. As discussed in connection with FIG.14, the volume of predictive purchase orders for a given item dependsupon the function that defines the predictive price discount versuspredictive order delay (POD). Therefore adjusting this function willimpact the volume of predictive purchase orders booked, which in turnaffects the consumption rate. When the control function is applied tothe real consumption, it induces a consumption corrective action thatcompensates for the consumption disturbance foreseen by the predictiveconsumption rates for the look forward interval. The expected resultwill be that the disturbance is significantly attenuated or possiblyeliminated and consumption progresses close to the desired baselineconsumption. The external consumption disturbances 1608 are illustratedin FIG. 16 by a broken line input to the real consumption 1607 toindicate that they represent unpredictable disturbances that are not anintegral part of the algorithmic closed loop control system 1600.

The ideal consumption from the perspective of manufacturers andproducers would be a consumption that increases gradually to reflectconsumption needs that can be fulfilled. However free market systems aresusceptible to consumption disturbances, often from uncontrollablefactors, which tend to trigger cyclic fluctuations.

To endure such fluctuations, manufacturers and producers have usedvarious strategies. One strategy is to maintain minimum inventorybuffers and gauge manufacturing resources for maximum consumption.During periods of high consumption, the manufacturer operates near fullcapacity at higher efficiency and generates higher earnings. However,during the periods of low consumption that typically follow, themanufacturer operates at low efficiency due to underutilized resourcesand generates lower earnings. Another strategy is to maintain largeinventory buffers and gauge manufacturing resources for averageconsumption. The large inventory buffers absorb the consumptionfluctuations but the cost of inventory results in reduced efficiency andearnings. Still another strategy is to maintain minimum inventorybuffers and gauge manufacturing resources for minimum consumption. Inthis case the manufacturer operates all the time at maximum efficiencyirrespectively of consumption fluctuations, but systematically losesbusiness to competitors because of the inability to met peak demand,thereby limiting growth opportunities, revenues, and earnings. For manyyears manufacturers and producers have tried a variety of strategies,but none has succeeded in overcoming the problems associated with cyclicfluctuations in consumption. To survive the effects of cyclic reductionsin consumption, sometimes manufacturers are forced to resort to drasticmeasures involving the reduction of valuable resources includingfacilities and personnel. Such measures tend to further aggravate theproblem and are typically the root cause of the deep economicfluctuations and recessions observed over the years.

FIGS. 17A-17B illustrate a consumption cruise control process 1700preferably performed by the algorithmic closed loop control system tostabilize consumption of an item based at least on consumption rateforecasts derived from predictive purchase orders booked for the item.

At step 1701, identifying the item to which the algorithmic closed loopcontrol process 1700 is applied.

At step 1702, identifying a time unit to express a time variable.

At step 1703, identifying a look back interval consisting of anidentified number of time units extending in time back from the end of acurrent time unit.

At step 1704, identifying a look forward interval consisting of anidentified number of time units extending in time forward from the endof the current time unit.

At step 1705, identifying a time window as a time interval obtained byappending the look forward interval to the look back interval.

At step 1706, identifying a control interval, wherein the controlinterval represents a time interval between two consecutive cycles ofthe algorithmic closed loop control process.

At step 1707, identifying a current control interval representing acycle of the algorithmic closed loop control process under execution.

At step 1708, identifying a baseline consumption rate of the item overthe time window, wherein the baseline consumption rate of the itemrepresents a disturbance free ideal consumption of the item per timeunit.

At step 1709, identifying a real consumption rate of the item over thelook back interval, wherein the real consumption rate of the itemrepresents the total quantity of the item acquired by consumers per timeunit.

At step 17010, identifying a look forward consumption rate of the itemover the look forward interval, wherein the look forward consumptionrate of the item represents a forecasted consumption rate of the itemderived from at least predictive purchase orders booked for the item.

At step 1711, collecting input data during a current control interval,wherein the input data includes:

-   -   (a) The baseline consumption rate over the time window.    -   (b) The real consumption rate over the look back interval.    -   (c) The look forward consumption rate over the look forward        interval.

At step 1712, executing control procedures at the end of the currentcontrol interval, wherein the control procedures include:

-   -   (a) Providing as inputs to the algorithmic closed loop        controller 1606 the input data collected during the current        control interval.    -   (b) Computing a control function to control the real consumption        1607 of the item during a control interval immediately        succeeding the current control interval, based at least on the        inputs provided to the algorithmic closed loop controller.        Preferably, the control function is computed by a software        program running in the algorithmic closed loop controller 1606.        The software program can be refined over time to take advantage        of the parametric inputs provided to the algorithmic closed loop        controller to try to maintain the real consumption rate as close        to the baseline consumption rate as possible. For example, the        software program can be configured with a parameter to reflect        consumer reaction time upon any changes in predictive price        discounts versus predictive order delay (POD), which can be        easily established empirically after the consumption cruise        control system is deployed. Consumer reaction time data can be        an important factor in optimizing the performance of the        algorithmic closed loop control system.    -   (c) Applying the computed control function to the real        consumption of the item.

At step 1713, repeating the steps of collecting input data and executingcontrol procedures in a loop.

The exemplary value previously suggested for the control interval wasone week based upon the traditional schedule used by grocery retailerswhereby promotional prices are typically adjusted on a given day eachweek. However, once consumers get used to programs that generatesuggested shopping lists and automatically execute online shopping, itmay be possible to shorten the control interval to a shorter value suchas one day resulting in improved response of the consumption cruisecontrol system.

D. Operation of the Consumer Preference Code Sub-System

The consumer preference code sub-system 104 was described in SectionII.D as a key system component of the supply-chain management system100. This section describes, with reference to FIGS. 18-20 theoperational features and methods associated with the consumer preferencecode sub-system 104.

FIG. 18 depicts an exemplary illustration of a web page 1800 that can beused by a consumer to set up preference codes for a non-uniform genericitem. The exemplary page displays the following:

-   -   a) A greeting field 1801 to welcome the consumer.    -   b) A generic item field 1802 for the consumer to enter the name        of a generic item for which the consumer wishes to set up        preference codes. For convenience, this field also provides a        pull down menu that allows the consumer to select the desired        generic item.    -   c) A personalized name field 1803 for the consumer to enter a        personalized name the consumer wishes to use to designate the        desired sub-class of the selected non-uniform generic item.    -   d) A table 1804 for the consumer to select the values for coded        characteristics that define the preferences of the consumer. The        left column of the table lists the name of each characteristic        used to define preference codes, the center column lists the        units used for each characteristic, and the right column        contains pull down menus from which the consumer can select the        desired value of each characteristic.    -   e) A save button 1805 that the user can click to store the        selected preference codes in the preference code database system        510.

FIG. 19 illustrates a preferred method 1900 for registering consumerpreference codes for a consumer in the consumer preference codesub-system 104.

At step 1901, identifying a consumer.

At step 1902, identifying a non-uniform generic item. The desirednon-uniform generic item can be identified by using a search programthat helps the user find the desired non-uniform generic item.

At step 1903, selecting preference codes for the identified non-uniformgeneric item based on the preferences of the consumer. For a first try,the consumer may start with pictures and descriptions that retailers mayprovide on the web. The consumer may also ask people who use similarcodes for a suggestion. Alternatively, the consumer can try to find at alocal retailer a sample of the desired item that meets the preferencesof the consumer and then ask the retailer for the preference codes ofthe sample.

At step 1904, obtaining a sample of the desired non-uniform generic itemusing the selected preference codes. A sample can be obtained by placingan order for small quantity of the desired item or from a merchant thatprovides samples.

At step 1905, inspecting the sample to determine whether or not thesample represents the preferences of the consumer.

At step 1906, iteratively repeating the steps of selecting preferencecodes, obtaining a sample, and inspecting the sample using for eachsucceeding iteration adjusted preference codes based upon the outcome ofprevious iterations until the sample represents the preferences of theconsumer. If the initially selected preference codes do not satisfy thepreferences of the consumer, adjusted preference codes can beiteratively selected that better reflect the preferences of theconsumer, based at least on the preference codes used in the previousiteration to the degree that such codes relate to the item received.Typically, the desired codes should be identifiable within a couple ofiterations.

At step 1907, storing the preference codes of the sample representingthe preferences of the consumer. Preferably the codes are stored in theconsumer data section 513 of the preference code database system 510,where they can be easily accessed by the consumer and by merchants.

FIG. 20 illustrates a preferred method 2000, for using the consumerpreference codes, whereby a consumer uses personalized referencesregistered under the name of the consumer to execute an online shoppingtransaction for a non-uniform generic item. For the purpose of thismethod it is assumed that the consumer is using a web browser to shoponline, even if the consumer is in a retail establishment. It is furtherassumed that the consumer is logged-on to a shopping platform configuredto support the use of the consumer preference code sub-system 104. Asdescribed in Section II.D in connection with the preference code webserver 520, a personalized reference program 522 is configured toreceive the identification of a consumer and the identification of ageneric name of a non-uniform generic item and return each of thepersonalized references associated with the generic name stored in thepreference code database system 510 under the name of the consumer.

At step 2001, recognizing the identification of the consumer shoppingonline. Once the consumer logs-in to a shopping platform configured tosupport the consumer preference code sub-system, the identification ofthe consumer is know to the preference code sub-system 104.

At step 2002, receiving from the consumer an identification of thenon-uniform generic item. The procedures by which consumers select itemsthey wish to purchase are part of the shopping platform operation andneed not be further described for the purpose of the present method.

At step 2003, displaying on the browser used by the consumer each of oneor more personalized references registered under the name of theconsumer for the identified non-uniform generic item. The personalizedreferences associated with the consumer for a given non-uniform genericitem are preferably stored in the consumer data section of thepreference code database system and should be readily available fordisplay on a web browser.

At step 2004, receiving from the consumer a selection of a personalizedreference from the one or more personalized references registered underthe name of the consumer.

At step 2005, completing the online shopping transaction for theselected generic item. Once the selected preference codes are receivedby the shopping platform the remaining portion of the shoppingtransaction is identical to that of any other item that does not involvethe selection of preference codes.

E. Operation of the Window Shop Management Sub-System

The window shop management sub-system 105 was described in Section II.Eas a key sub-system component of the supply-chain management system 100.This section describes, with reference to FIGS. 21A-C a preferred methodfor the operation of the window shop management sub-system 105 and thewindow shops 806 managed by the window shop management sub-system. Theoperational method addresses functions performed for the benefit of bothmerchants 801 and consumers 805. Manufacturers, producers, and serviceproviders are the primary merchants deriving benefits from the windowshop management sub-system because of the advantages offered by thewindow shop model for the promotion of products and services.

At step 2101, identifying a plurality of window shops 806 participatingin the window shop management sub-system 105. It is expected that everycommercial establishment interested in operating a window shop will be aparticipant and preferably the window shop management sub-system 105will provide a service to assist commercial establishments in becomingparticipants.

At step 2102, identifying window shop data for each participating windowshop.

At step 2103, storing and maintaining the identified window shop datafor each participating window shop. Each window shop can assumeresponsibility for entering and maintaining the window shop data,related to the window shop, in the window shop database system 611.Alternatively, any other method to enter the window shop data in thewindow shop database system 611 can be used provided the window shopdatabase system 611 is maintained current.

At step 2104, responding to queries related to window shop data.

At step 2105, providing a web based promotion and advertising programconfigured to promote and advertise window shop services to merchants.Preferably, the promotion and advertising program is configured forwindow shops to target merchants that may have an interest in the areasof specialization of the window shop.

At step 2106, providing a web based browsing program configured toprovide browsing web pages to view and browse window shop data. Thisprogram can be used by a merchant to evaluate and compare window shopsand facilitate the selection of window shops best suited to provideservices to the merchant.

At step 2107, providing a web based search engine program configured tomatch given merchant requirements for window shop facilities andservices with each identified window shop configured to fulfill thegiven merchant requirements. In a preferred embodiment, a search enginecan accept as inputs a set of merchant requirements expressed in astandardized form through menu selections and based on the inputs thesearch engine can scan the window shop database system 611 to identifythe window shops that match the merchant requirements.

At step 2108, providing a web based window shop reservation programconfigured to accept reservations for window shop facilities andservices from merchants for a given period of time in one or moregeographic locations. In a preferred embodiment, the window shop webserver 621 is configured to provide a window shop and decentralizedexhibition reservation program to reserve window shop services for thebenefit of merchants.

At step 2109, providing a web based brokerage program configured toexecute booking transactions between merchants and window shops. In apreferred embodiment, the window shop web server 621 is configured toprovide a window shop brokerage program to execute booking transactionsbetween merchants and window shops for facilities and services providedby window shops. The procedures of booking transactions can typically beaddressed by the brokerage program, but human assistance may be requiredto address specific details that may not be anticipated by the brokerageprogram.

At step 2110, advertising the window shop services to the merchants. Ina preferred embodiment, the major methods of advertising includeInternet and direct email. Alternatively, the window shop managementsub-system can take advantage of the universal directory of merchantsthat participate in the supply-chain management system and the universaldirectory of original manufacturers, producers, and service providers,introduced earlier at the end of Section II.F to implement targetadvertising programs.

At step 2111, informing consumers of the identified plurality of windowshops. Methods for informing consumers of the window shops in theirregion can include the following:

-   -   (a) Internet advertising.    -   (b) Direct email.    -   (c) Local media advertising.    -   (d) Promotional incentives for consumers to visit the window        shops, such as promotional gifts and price discounts.    -   (e) Promotional amenities such as coffee bar, Internet access,        light entertainment, etc.

At step 2112, providing a search engine program configured to associatean item with window shops representing the item. Preferably, the searchengine program is based upon the universal catalog of items (productsand services), introduced earlier at the end of Section II.F.

At step 2113, providing a window shop locator program. In a preferredembodiment, the locator program is the window shop locator applicationprogram executable on the window shop web server 621 as indicated inSection II.E. The locator utility can be of use to both consumers andmerchants for locating window shops of interest.

At step 2114, instructing the identified window shops to provideinformation and assistance to consumers visiting the identified windowshops. Preferably, the window shops are staffed with personnel qualifiedto explain item features, give demonstrations, answer consumerinquiries, provide technical support, provide consumer training, andassist consumers with the selection of items and order placement.

At step 2115, instructing the identified window shops to collectconsumer information related to items consumers may be interested inacquiring. The primary function of the window shop personnel is toproperly inform consumers about items represented by the window shop. Inthe exercise of this function, the window shop personnel have a uniqueopportunity to obtain from consumers extremely valuable informationrelated to items consumers may be interested in acquiring, as previouslyindicated in Section I.D.

At step 2116, providing the consumer information collected by the windowshop, related to an item promoted by the window shop, to the merchantholding a contract with the window shop to promote the item. Asindicated in Section II.E, the window shop management sub-system cancompile and summarize the consumer information collected by each windowshop and for each item promoted by the window shop communicate thecompiled and summarized consumer information to the merchant thatretained the window shop to promote the item.

At step 2117, instructing the window shops to book purchase orders fromconsumers who decide to place purchase orders with the window shop. Asdescribed in Section II.E, purchase orders from consumers that visit awindow shop can be booked with the web server running the online orderbooking platform 632.

F. Operation of the Supply-Chain Management Sub-System

The supply-chain management sub-system 105, described earlier in SectionII.F, is the basic integrating and coordinating component of thesupply-chain management system 100. It integrates and coordinates theoperations of the sub-systems described earlier in sections II.A throughII.E and provides additional resources that support the operation of thesupply-chain management system 100.

This section describes, with reference to FIGS. 22A-B a method 2200preferably performed by the supply-chain management sub-system.

At step 2201, identifying a plurality of merchants participating in thesupply-chain management sub-system. The identification of the pluralityof merchants can de derived from the universal directory of merchantsthat participate in the supply-chain management sub-system describedearlier in Section II.F.

At step 2202, identifying a plurality of different items, whereby eachdifferent item is provided by at least one of the identified merchants.The identification of the items can de derived from the universalcatalog of items (products and services) described earlier in SectionII.F.

At step 2203, for each identified different item, storing item datacharacterizing the item. Preferably the item data for each item isstored in the item information database system 703 and includes theinformation normally used by merchants to promote and sell the item toconsumers.

At step 2204, for each identified merchant collecting and storing inreal-time inventory data. Preferably, the inventory data for each of themerchants includes the data described earlier in Section II.F inconnection with the inventory management database systems 701.

At step 2205, for each identified merchant collecting and storing,booked order data for each predictive and non-predictive purchase orderbooked by the merchant. Preferably, orders are entered in the orderhistory database systems 702 in real-time upon completion of the bookingprocess.

At step 2206, providing web servers configured to operate onlineshopping platforms supporting online consumer shopping activities. Asindicated earlier, these web servers are provided as a convenience formerchants that are not equipped to offer consumers online shoppingservices and will facilitate the transition of these merchants into thesupply-chain management sub-system.

At step 2207 providing web servers configured to operate online orderbooking platforms supporting online order booking activities. Asindicated earlier, these web servers are provided as a convenience formerchants that are not equipped to operate online order booking servicesand will facilitate the transition of these merchants into thesupply-chain management sub-system.

At step 2208, providing web servers configured to operate consumptionmonitoring platforms for collecting and compiling consumption monitoringdata in real-time and generating consumption forecasts for at least oneidentified different item. Preferably, consumption data will beavailable to all participants of the supply-chain management system asan information service.

At step 2209, informing each identified merchant providing an identifieddifferent item of consumption forecasts generated for the item. Theconsumption forecasts can be derived from the booked order data by theconsumption forecasting programs operated by the predictive orderingsub-system as described earlier in Section II.C.

At step 2210, providing web servers configured to operate real-timefinancial transaction execution platforms to execute financialtransactions between entities participating in the supply-chainmanagement sub-system. The supply-chain management sub-system 105 canprovide cost effective financial transaction execution platforms tofacilitate and encourage the participation of all entities involved inthe supply-chain from source manufacturers, producers, and serviceproviders at the beginning link of the supply-chain to the consumers atthe ending link of the supply-chain.

This section completes the description of the operation of thesupply-chain management system 100. The description attempted toemphasize the functional aspects of the supply-chain management systemin connection with logical integration of the various functions, each ofwhich plays an important role in the efficient operation of thesupply-chain management system. Actual implementations may deviatesignificantly from the various illustrations and examples used in thisspecification, mostly as a consequence of cost saving benefits and otherpractical considerations. All such implementations are within the scopeof the invention disclosed in this specification.

IV. CONCLUSION

While certain preferred embodiments have been described and shown in theaccompanying drawings, it is to be understood that such embodiments aremerely illustrative of, and not restrictive on, the broad invention.Other embodiments that are apparent to those of ordinary skill in theart, including embodiments that do not provide all of the features andadvantages set forth herein, are also within the scope of thisinvention. Further, it is to be understood that this invention is notlimited to the specific construction and arrangements shown anddescribed since various modifications or changes may occur to those ofordinary skill in the art without departing from the spirit and scope ofthe invention. Accordingly, the scope of the invention is defined by theclaims that follow. In the claims, a portion shall include greater thannone and up to the whole of a thing. In the method claims, referencecharacters are used for convenience of description only, and do notindicate a particular order for performing the method.

1. A supply-chain management system comprising: an Internet-based orderaggregation management sub-system executing on a computer systemconfigured to manage activities associated with transfers of items froma plurality of merchants to a plurality of consumers, wherein each ofthe plurality of consumers purchases at least one item designated forphysical aggregation from a different one of the plurality of merchants,and wherein items designated for physical aggregation, purchased by eachconsumer, are sent to an identified order aggregation facility proximatethe consumer to be physically aggregated in one or more batches inaccordance with provided aggregation instructions, wherein each batch ofphysically aggregated items is transferred from the identified orderaggregation facility to the consumer who purchased the items at anidentified date and time; an Internet-based integrated inventory sharingsub-system executing on a computer system configured to reduce requiredoperating inventories of merchants, balance inventories, reduceinventory costs, and fulfill consumer orders in real time based uponpre-planned regional inventory positions, wherein a plurality ofmerchants participating in the Internet-based integrated inventorysharing sub-system share inventories to create a virtual inventory, andwherein each merchant is provided access to the Internet-basedintegrated inventory sharing sub-system to execute an inventory relatedtransaction with another merchant of said plurality of merchants, basedat least upon the virtual inventory; an Internet-based predictiveordering consumption forecasting sub-system executing on a computersystem configured to support predictive purchase orders placed by aplurality of consumers with a plurality of merchants, wherein apredictive purchase order for an item subject to a predictive pricediscount is characterized by a consumer receiving the predictive pricediscount in exchange for placing the predictive purchase order for theitem with a merchant at an order date and accepting delivery at a laterdelivery date, wherein a predictive order delay, representing a timespan between the order date and the delivery date, determines thepredictive price discount applied to the item, based at least upon costsavings realized by the supply-chain as a result of forecastedconsumption rates for the item derived from at least predictive purchaseorders booked, and wherein the predictive ordering consumptionforecasting sub-system communicates the forecasted consumption rates toan Internet-based supply-chain management sub-system; an Internet-basedconsumer preference code sub-system executing on a computer systemconfigured for identifying a plurality of sub-classes of items within aclass of non-uniform generic items known by consumers by a generic namewherein the items in each sub-class are representative of a differentone of a plurality of identified preferences of consumers and whereinthe Internet-based consumer preference code sub-system is furtherconfigured for a consumer to shop online for an item of a specificsub-class of the class of non-uniform generic items by using adesignation comprising the generic name of the item and codes thatidentify the specific sub-class of the item; an Internet-based windowshop management sub-system executing on a computer system configured toprovide operational management for a plurality of window shops, whereina window shop is an inventory-less commercial establishment configuredto provide display space and facilities where merchants display,promote, present, and launch items purchased by consumers and whereconsumers are able to make selections and decisions with respect toitems they may be interested in acquiring, and wherein the window shopis staffed with personnel qualified to assist consumers by explainingitem features, giving demonstrations, answering consumer inquiries,providing technical support and customer service, providing consumertraining, and helping consumers with selection of items and orderplacement; and an Internet-based supply-chain management sub-systemexecuting on a computer system configured to integrate the orderaggregation management sub-system, the integrated inventory sharingsub-system, the predictive ordering consumption forecasting sub-system,the consumer preference code sub-system and the window shop managementsub-system to manage a just-in-time distribution of items purchased bythe plurality of consumers from the plurality of merchants, wherein thesupply-chain management subsystem tracks and manages inventory levelsand inventory reductions in the supply-chain and provides consumptionstatistics and forecasts to the plurality of merchants.
 2. Thesupply-chain management system of claim 1, wherein the Internet-basedorder aggregation management sub-system comprises: an aggregationmanagement database system executing on a computer system, wherein theaggregation management database system is configured to storeaggregation management data, the aggregation management data comprising:merchant data; purchase order data; aggregation and delivery data; orderaggregation facility data; carrier data; and transportation data; anorder aggregation web server executing on a computer system, wherein theorder aggregation web server is configured to access the aggregationmanagement database system and to execute application programs to managetasks associated with transfers of items from the plurality of merchantsto the plurality of consumers, based at least on the aggregationmanagement data, the application programs comprising: a data entry andretrieval program; a report generation program; an activity schedulingprogram; and a carrier service request generation program; and a carriermanagement web server executing on a computer system, wherein thecarrier management web server is configured to access the aggregationmanagement database system and to execute application programs to managetasks associated with the transportation operations of a plurality ofcarriers used to provide carrier services coordinated by theInternet-based order aggregation management sub-system, based at leaston the stored aggregation management data, the application programscomprising: a service request management program; a carrier managementprogram; and a delivery scheduling program.
 3. The supply-chainmanagement system of claim 2, wherein the Internet-based orderaggregation management sub-system is configured to: identify a pluralityof consumers using the supply-chain management system for shopping;identify a plurality of merchants participating in the supply-chainmanagement system; identify a plurality of order aggregation facilitiesparticipating in the supply-chain management system; identify for eachconsumer of the identified consumers items purchased by the consumerfrom the identified merchants, wherein the items are designated foraggregation in a batch; identify for each consumer of the identifiedconsumers an order aggregation facility where the items in the batchwill be physically aggregated; identify for each consumer of theidentified consumers order aggregation instructions for the items in thebatch to be physically aggregated; identify for each consumer of theidentified consumers a date and time for transferring the batch ofphysically aggregated items to the consumer; identify for each orderaggregation facility of the identified order aggregation facilitiesaggregation schedules compliant with order aggregation instructions forthe batches of items to be physically aggregated by the orderaggregation facility; instruct each merchant of the identified merchantsto group the items purchased by consumers in separate groups, whereineach group consists of items to be physically aggregated at a sameidentified order aggregation facility at proximate times; instruct eachmerchant of the identified merchants to ship each of the separate groupsof items to said same identified order aggregation facility just-in-timein compliance with the aggregation schedules for the items to beaggregated at said same order aggregation facility; provide to each ofthe identified order aggregation facilities the identified orderaggregation instructions for each consumer scheduled to receive aphysically aggregated batch from the order aggregation facility;instruct each of the identified order aggregation facilities toaggregate the items received from the merchants in accordance with theprovided aggregation instructions for each consumer; instruct each ofthe identified order aggregation facilities to transfer to each of theconsumers scheduled to receive a batch of physically aggregated itemsdesignated for pick up the batch of physically aggregated items at theidentified date and time; and instruct each of the identified orderaggregation facilities to deliver to each of the consumers scheduled toreceive a batch of physically aggregated items designated for deliverythe batch of physically aggregated items at the identified date and timeto an address designated by the consumer.
 4. The supply-chain managementsystem of claim 1, wherein the Internet-based integrated inventorysharing sub-system comprises: an inventory sharing database systemexecuting on a computer system, wherein the inventory sharing databasesystem is configured to store inventory sharing data, the inventorysharing data comprising: merchant sharing data; and virtual inventorydata; and a virtual inventory web server executing on a computer system,wherein the virtual inventory web server is configured to access theinventory sharing database system and to execute application programs tooperate the Internet-based integrated inventory sharing sub-system, theapplication programs comprising: a data entry and retrieval program; amaintenance program; a query program; a transaction processing program;and a market making program.
 5. The supply-chain management system ofclaim 4, wherein the Internet-based integrated inventory sharingsub-system is configured to: identify a plurality of merchantsparticipating in the Internet-based integrated inventory sharingsub-system; identify the merchant sharing data of the identifiedmerchants; store the merchant sharing data of the identified merchants;compute the virtual inventory data based at least on the merchantsharing data of the identified merchants; store the computed virtualinventory data; update in real-time the virtual inventory data upon achange of the merchant sharing data of a merchant of the identifiedmerchants; respond in real-time to queries related to virtual inventorydata and merchant sharing data; generate a bid and ask market tofacilitate transactions among the identified merchants by matching inreal-time bid prices and quantities provided by one merchant for a givenitem to ask prices and quantities provided by another merchant for thegiven item; and execute and process inventory transactions performed byand between the identified merchants.
 6. The supply-chain managementsystem of claim 1, wherein the Internet-based predictive orderingconsumption forecasting sub-system comprises: a predictive orderingdatabase executing on a computer system, wherein the predictive orderingdatabase is configured to store predictive ordering data for eachmerchant of a plurality of merchants participating in the Internet-basedpredictive ordering consumption forecasting sub-system, the predictiveordering data comprising: cost saving data; predictive discount data;real consumption data; and forecasted consumption data; and a predictiveordering web server executing on a computer system, wherein thepredictive ordering web server is configured to access the predictiveordering database and to execute application programs to operate theInternet-based predictive ordering consumption forecasting sub-system,the application programs comprising: a data entry and retrieval program;a cost savings program; a real consumption monitoring program; and aconsumption forecasting program.
 7. The supply-chain management systemof claim 6, wherein the Internet-based predictive ordering consumptionforecasting sub-system is configured to: identify an item subject to apredictive price discount; identify a plurality of consumers, whereineach consumer uses predictive purchase orders to shop for the itemsubject to a predictive price discount; identify at least one merchantproviding the item subject to the predictive price discount; identify apredictive discount schedule of predictive price discount versuspredictive order delay applicable to the item; inform the at least onemerchant of the predictive discount schedule applicable to the item;inform each of the identified consumers of the predictive discountschedule applicable to the item; generate consumption forecasts for theitem, wherein the consumption forecasts for the item are based at leastupon predictive purchase orders booked for the item, analyzed realconsumption data for the item, and historical correlations betweenpredictive and non-predictive purchase orders booked for the item; andinform in real-time the at least one merchant of consumption forecastsgenerated for the item.
 8. The supply-chain management system of claim7, wherein the Internet-based predictive ordering consumptionforecasting sub-system is further configured to: associate with the itemvariables expressing predictive order volume, predictive order delay,and predictive price discount; define a first function associated withthe item correlating the variables predictive order volume, predictiveorder delay, and predictive price discount; identify a parameterassociated with the item that is affected by said first function; definea second function that correlates the identified parameter to said firstfunction; based at least on said second function, identify a predictivediscount schedule of predictive price discount versus predictive orderdelay that optimizes the parameter associated with the item; and applythe identified predictive discount schedule to the item.
 9. Thesupply-chain management system of claim 6, wherein the Internet-basedpredictive ordering consumption forecasting sub-system further comprisesan algorithmic closed loop control process to minimize or avertundesirable disturbances in consumption, the algorithmic closed loopcontrol process comprising: identifying an item, wherein the algorithmicclosed loop control process is applied to the item; identifying a timeunit to express a time variable; identifying a look back interval;identifying a look forward interval; identifying a time window;identifying a control interval; identifying a current control interval;identifying a baseline consumption rate of the item; identifying a realconsumption rate of the item; identifying a look forward consumptionrate of the item; collecting input data during a current controlinterval, wherein the input data comprise: the baseline consumptionrate; the real consumption rate; and the look forward consumption rate;executing control procedures at the end of the current control interval,wherein the control procedures comprise: providing as inputs to thealgorithmic closed loop controller the input data collected during thecurrent control interval; computing a control function to control thereal consumption of the item during a control interval immediatelysucceeding the current control interval, based at least on the inputdata provided to the algorithmic closed loop controller; and applyingthe computed control function to the real consumption of the item; andrepeating the steps of collecting input data and executing controlprocedures in a continuous loop.
 10. The supply-chain management systemof claim 1, wherein the Internet-based consumer preference codesub-system comprises: a preference code database executing on a computersystem, wherein the preference code database stores preference code datafor each class of a plurality of different classes of non-uniformgeneric items identified by a generic name purchased by consumers,wherein for each class of the plurality of different classes ofnon-uniform generic items the preference code data comprise: class data;sub-class data; and consumer data; and a preference code web serverexecuting on a computer system, wherein the preference code web serveris configured to access the preference code database and to executeapplication programs to operate the Internet-based consumer preferencecode sub-system, the application programs comprising: a data entry andretrieval program; a personalized reference program; a consumerpreference code subscription program; a consumer preference coderegistration program; and an interface program for the consumer to usepreference codes.
 11. The supply-chain management system of claim 10,wherein the consumer preference code registration program is configuredto: identify a consumer; identify a non-uniform generic item; selectpreference codes for the identified non-uniform generic item based onpreferences of the consumer; obtain a sample of the desired non-uniformgeneric item using the selected preference codes; inspect the sample todetermine whether or not the sample represents the preferences of theconsumer; iteratively repeat the steps of selecting preference codes,obtaining a sample, and inspecting the sample using for each succeedingiteration adjusted preference codes based upon the outcome of previousiterations until the sample represents the preferences of the consumer;and store the preference codes of the sample representing thepreferences of the consumer.
 12. The supply-chain management system ofclaim 10, wherein the interface program for the consumer to usepreference codes is configured to: recognize an identification of aconsumer shopping online; receive from the consumer an identification ofa non-uniform generic item; display on a browser used by the consumereach of one or more preference codes registered in the name of theconsumer for the identified non-uniform generic item; receive from theconsumer a selection of a preference code from the one or morepreference codes registered in the name of the consumer; and completethe online shopping transaction for the identified generic item.
 13. Thesupply-chain management system of claim 1, wherein the Internet-basedwindow shop management sub-system comprises: a window shop databaseexecuting on a computer system, wherein the window shop database isconfigured to store window shop data for each window shop of theplurality of window shops; a window shop web server executing on acomputer system, wherein the window shop web server is configured toaccess the window shop database and to execute application programs tomanage tasks associated with the operation of each window shop of theplurality of window shops, the application programs comprising: a dataentry and retrieval program; a web-based promotion and advertisingprogram; a browsing program configured to provide browsing web pages toview and browse window shop data; a search engine program; a window shopreservation program; a window shop brokerage program; and a window shoplocator program; a web server running an online shopping platformexecuting on a computer system, wherein the web server running an onlineshopping platform is configured to support consumer online shopping; anda web server running an online order booking platform executing on acomputer system, wherein the web server running an online order bookingplatform is configured to support order booking and processing servicesfor booking and processing purchase orders placed by consumers.
 14. Thesupply-chain management system of claim 13, wherein the Internet-basedwindow shop management sub-system and the window shops managed by theInternet-based window shop management sub-system are configured to:identify a plurality of window shops participating in the supply-chainmanagement system; identify window shop data for each window shop of theparticipating window shops; store and maintain the identified windowshop data; respond to queries related to window shop data; provide a webbased promotion and advertising program, executing on a computer system,configured to promote and advertise window shop services to merchants;provide a web based browsing program, executing on a computer system,configured to provide browsing web pages to view and browse window shopdata; provide a web based search engine program, executing on a computersystem, configured to match given merchant requirements for window shopservices with each identified window shop configured to fulfill thegiven merchant requirements; provide a web based window shop reservationprogram, executing on a computer system, configured to acceptreservations for window shop services; provide a web based brokerageprogram, executing on a computer system, configured to execute bookingtransactions between merchants and window shops; provide a window shoplocator program executing on a computer system; instruct the identifiedwindow shops to provide information and assistance to consumers visitingthe identified window shops; instruct the identified window shops tocollect consumer information related to items consumers may beinterested in acquiring; provide consumer information collected by awindow shop related to an item promoted by the window shop to a merchantholding a contract with the window shop to promote the item; andinstruct the window shops to book purchase orders from consumersdeciding to place purchase orders with the window shop.
 15. Thesupply-chain management system of claim 1, wherein the Internet-basedsupply-chain management sub-system comprises: an inventory managementdatabase executing on a computer system, wherein the inventorymanagement database is configured to store merchant inventory data foreach merchant of the plurality of merchants; an order history databaseexecuting on a computer system, wherein the order history database isconfigured to store booked order data; an item information databaseexecuting on a computer system, wherein the item information database isconfigured to store item data for each item provided by at least onemerchant of the plurality of merchants, wherein the item datacharacterizes the item; at least one web server running an onlineshopping platform executing on a computer system, wherein the web serverrunning an online shopping platform is configured to provide web pagesfor supporting a plurality of online shopping activities that facilitateonline shopping by the plurality of consumers from the plurality ofmerchants; at least one web server running an online order bookingplatform executing on a computer system, wherein the web server runningan online order booking platform is configured to provide merchants withonline order booking services; at least one web server running areal-time consumption monitoring platform executing on a computersystem, wherein the web server running a real-time consumptionmonitoring platform is configured to execute programs to collect andcompile consumption monitoring data in real-time and generateconsumption forecasts for each item of a plurality of items based atleast on purchase orders booked for the item by each merchant of theplurality of merchants; at least one web server running a real-timefinancial transaction integrated platform executing on a computersystem, wherein the web server running a real-time financial transactionintegrated platform is configured to execute financial transactionsamong entities participating in the supply-chain management system toreduce execution times and costs associated with the financialtransactions.
 16. The supply-chain management system of claim 15,wherein the Internet-based supply-chain management sub-system isconfigured to: identify a plurality of merchants participating in thesupply-chain management system; identify a plurality of different items,wherein each different item is provided by at least one of theidentified merchants; for each identified different item, store itemdata characterizing the item; for each identified merchant collect andstore in real-time inventory data; for each identified merchant collectand store in real-time, booked order data for predictive andnon-predictive purchase orders booked by the merchant; provide webservers executing on a computer system, wherein the web servers areconfigured to operate online shopping platforms supporting onlineconsumer shopping activities; provide web servers executing on acomputer system, wherein the web servers are configured to operateonline order booking platforms supporting online order bookingactivities; provide web servers executing on a computer system, whereinthe web servers are configured to operate consumption monitoringplatforms for collecting and compiling consumption monitoring data inreal-time and generating consumption forecasts for at least oneidentified different item; inform each identified merchant providing anidentified different item of consumption forecasts generated for theitem; and provide web servers executing on a computer system, whereinthe web servers are configured to operate real-time financialtransaction execution platforms to execute financial transactionsbetween entities participating in the supply-chain management system.17. An Internet-based predictive ordering consumption forecasting systemthat uses price discounts to motivate consumers to participate, theInternet-based predictive ordering consumption forecasting systemcomprising: a predictive ordering database executing on a computersystem, wherein the predictive ordering database is configured to storepredictive ordering data associated with predictive purchase ordersplaced by consumers with merchants, wherein a predictive purchase orderfor an item is characterized by a consumer receiving a predictive pricediscount in exchange for placing the predictive purchase order for theitem with a merchant at an order date and accepting delivery at a laterdelivery date, wherein a predictive order delay, representing a timespan between the order date and the delivery date, determines thepredictive price discount applied to the item, based at least upon costsavings realized as a result of forecasted consumption rates for theitem derived from at least predictive purchase orders booked, andwherein the predictive ordering consumption forecasting systemcommunicates the forecasted consumption rates to a supply-chain system,the predictive ordering database storing: cost saving data representingcosts savings realized based at least on forecasted consumption ratesderived from predictive purchase orders booked; predictive discount datacomprising an identification of price discounts versus predictive orderdelay; real consumption data comprising actual consumption derived fromdelivered purchases; and forecasted consumption data comprisingforecasted consumption based at least upon predictive purchase ordersbooked, analyzed real consumption data, and historical correlationsbetween predictive and non-predictive purchase orders booked; and apredictive ordering web server executing on a computer system, whereinthe predictive ordering web server is configured to access thepredictive ordering database and to execute application programs tosupport predictive ordering, the application programs comprising: a dataentry and retrieval program configured to enter and maintain predictiveordering data in the predictive ordering database and to respond toqueries; a cost savings program configured to estimate, for itemssubject to the predictive price discount, a cost savings realized by thesupply-chain versus the predictive order delay; a real consumptionmonitoring program configured to analyze real consumption data; and aconsumption forecasting program configured to generate consumptionforecasts based at least upon predictive purchase orders booked,analyzed real consumption data, and identified correlation factorsbetween predictive and non-predictive purchase orders booked.
 18. AnInternet-based predictive ordering consumption forecasting methodexecuting on a computer system, the Internet-based predictive orderingconsumption forecasting method comprising: identifying a plurality ofconsumers, wherein each consumer uses predictive ordering to shop foritems subject to a predictive price discount, wherein predictiveordering is characterized by a consumer receiving the predictive pricediscount in exchange for placing a predictive purchase order for an itemsubject to the predictive price discount at an order date and acceptingdelivery at a later delivery date wherein a predictive order delay,representing a time span between the order date and the delivery date,determines the predictive price discount, based at least upon costsavings realized as a result of forecasted consumption rates derivedfrom at least predictive purchase orders booked, and wherein thepredictive ordering consumption forecasting system communicates theforecasted consumption rates to a supply-chain system; identifying anitem subject to wherein a predictive price discount; identifying atleast one merchant providing the item subject to the predictive pricediscount; identifying a predictive discount schedule of predictive pricediscount versus predictive order delay applicable to the item; informingthe at least one merchant of the predictive discount schedule applicableto the item; informing the identified consumers of the predictivediscount schedule applicable to the item; generating consumptionforecasts for the item, wherein the consumption forecasts for the itemare based at least upon predictive purchase orders booked for the item,analyzed real consumption data for the item, and historical correlationsbetween predictive and non-predictive purchase orders booked for theitem; and informing in real-time the at least one merchant ofconsumption forecasts generated for the item.
 19. The Internet-basedpredictive ordering consumption forecasting method of claim 18, furthercomprising: associating with the item variables expressing predictiveorder volume, predictive order delay, and predictive price discount;defining a first function associated with the item, the first functioncorrelating the variables predictive order volume, predictive orderdelay, and predictive price discount; identifying a parameter associatedwith the item wherein the parameter is affected by said first function;defining a second function, the second function correlating theidentified parameter to said first function; based at least on thesecond function, identifying a predictive discount schedule ofpredictive price discount versus predictive order delay that optimizesthe parameter associated with the item; and applying the identifiedpredictive discount schedule to the item.
 20. The Internet-basedpredictive ordering consumption forecasting method of claim 19, furthercomprising an algorithmic closed loop consumption control process tominimize or avert undesirable disturbances in the consumption of anitem, the algorithmic closed loop consumption control processcomprising: identifying an item, wherein the algorithmic closed loopcontrol process is applied to the item; identifying a time unit toexpress a time variable; identifying a look back interval defined as atime interval expressed in time units extending in time back from theend of a current time unit; identifying a look forward interval definedas a time interval expressed in time units, extending in time forwardfrom the end of a current time unit; identifying a time window obtainedby appending the look forward interval to the look back interval;identifying a control interval defined as a time interval between twoconsecutive cycles of the algorithmic closed loop control algorithm;identifying a current control interval defined as the control intervalassociated with a cycle of the algorithmic closed loop control algorithmbeing executed; identifying a baseline consumption rate of the itemdefined as a variable representing a disturbance free ideal consumptionof the item per time unit; identifying a real consumption rate of theitem defined as a total quantity of the item acquired by consumers pertime unit; identifying a look forward consumption rate of the itemdefined as a variable representing a projected consumption rate of theitem versus time over the look forward interval; collecting input dataduring the current control interval, wherein the input data comprise:the baseline consumption rate; the real consumption rate; and the lookforward consumption rate; executing control procedures at the end of thecurrent control interval, wherein the control procedures comprise:providing as inputs to the algorithmic closed loop controller the inputdata collected during the current control interval; computing a controlfunction to control the real consumption of the item during a controlinterval immediately succeeding the current control interval, based atleast on the input data provided to the algorithmic closed loopcontroller wherein the control function expresses an appropriate levelof control action necessary to maintain the real consumption of the itemclose to the baseline consumption; applying the computed controlfunction to the real consumption of the item; and repeating the steps ofcollecting input data and executing control procedures in a continuousloop.